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Update README.md
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README.md
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@@ -3,452 +3,453 @@ license: llama2
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language:
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- ro
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base_model: meta-llama/Llama-2-7b-hf
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model-index:
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- name: OpenLLM-Ro/RoLlama2-7b-Base-2024-05-14
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results:
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- task:
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type: text-generation
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dataset:
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name: Romanian_Academic_Benchmarks
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type: Romanian_Academic_Benchmarks
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metrics:
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- name: Average accuracy
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type: accuracy
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value: 38.03
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_arc_challenge
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type: OpenLLM-Ro/ro_arc_challenge
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metrics:
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- name: Average accuracy
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type: accuracy
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value: 37.95
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_mmlu
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type: OpenLLM-Ro/ro_mmlu
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metrics:
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- name: Average accuracy
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type: accuracy
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value: 27.22
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_winogrande
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type: OpenLLM-Ro/ro_winogrande
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metrics:
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- name: Average accuracy
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type: accuracy
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value: 59.29
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_hellaswag
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type: OpenLLM-Ro/ro_hellaswag
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metrics:
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- name: Average accuracy
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type: accuracy
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value: 57.22
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_gsm8k
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type: OpenLLM-Ro/ro_gsm8k
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metrics:
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- name: Average accuracy
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type: accuracy
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value: 2.53
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_truthfulqa
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type: OpenLLM-Ro/ro_truthfulqa
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metrics:
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- name: Average accuracy
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type: accuracy
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value: 44
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- task:
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type: text-generation
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dataset:
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name: LaRoSeDa_binary
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type: LaRoSeDa_binary
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metrics:
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- name: Average macro-f1
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type: macro-f1
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value: 83.25
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- task:
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type: text-generation
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dataset:
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name: LaRoSeDa_multiclass
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type: LaRoSeDa_multiclass
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metrics:
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- name: Average macro-f1
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type: macro-f1
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value: 61.04
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- task:
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type: text-generation
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dataset:
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name: LaRoSeDa_binary_finetuned
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type: LaRoSeDa_binary_finetuned
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metrics:
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- name: Average macro-f1
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type: macro-f1
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value: 98.97
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- task:
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type: text-generation
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dataset:
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name: LaRoSeDa_multiclass_finetuned
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type: LaRoSeDa_multiclass_finetuned
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metrics:
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- name: Average macro-f1
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type: macro-f1
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value: 87.72
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- task:
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type: text-generation
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dataset:
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name: WMT_EN-RO
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type: WMT_EN-RO
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metrics:
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- name: Average bleu
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type: bleu
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value: 10.01
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- task:
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type: text-generation
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dataset:
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name: WMT_RO-EN
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type: WMT_RO-EN
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metrics:
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- name: Average bleu
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type: bleu
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value: 13.03
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- task:
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type: text-generation
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dataset:
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name: WMT_EN-RO_finetuned
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type: WMT_EN-RO_finetuned
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metrics:
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- name: Average bleu
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type: bleu
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value: 27.85
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- task:
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type: text-generation
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dataset:
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name: WMT_RO-EN_finetuned
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type: WMT_RO-EN_finetuned
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metrics:
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- name: Average bleu
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type: bleu
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value: 39.3
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- task:
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type: text-generation
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dataset:
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name: XQuAD
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type: XQuAD
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metrics:
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- name: Average exact_match
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type: exact_match
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value: 30.15
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- task:
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type: text-generation
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dataset:
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name: XQuAD
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type: XQuAD
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metrics:
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- name: Average f1
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type: f1
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value: 47.03
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- task:
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type: text-generation
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dataset:
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name: XQuAD_finetuned
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type: XQuAD_finetuned
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metrics:
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- name: Average exact_match
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type: exact_match
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value: 67.06
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- task:
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type: text-generation
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dataset:
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name: XQuAD_finetuned
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type: XQuAD_finetuned
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metrics:
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- name: Average f1
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type: f1
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value: 79.96
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- task:
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type: text-generation
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dataset:
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name: STS
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type: STS
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metrics:
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- name: Average spearman
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type: spearman
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value: 7.89
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- task:
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type: text-generation
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dataset:
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name: STS
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type: STS
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metrics:
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- name: Average pearson
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type: pearson
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value: 7.98
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- task:
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type: text-generation
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dataset:
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name: STS_finetuned
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type: STS_finetuned
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metrics:
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- name: Average spearman
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type: spearman
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value: 71.75
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- task:
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type: text-generation
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dataset:
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name: STS_finetuned
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type: STS_finetuned
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metrics:
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- name: Average pearson
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type: pearson
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value: 71.99
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_arc_challenge
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type: OpenLLM-Ro/ro_arc_challenge
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metrics:
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- name: 0-shot
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type: accuracy
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value: 35.56
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- name: 1-shot
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type: accuracy
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value: 36.42
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- name: 3-shot
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type: accuracy
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value: 38.56
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- name: 5-shot
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type: accuracy
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value: 38.39
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- name: 10-shot
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type: accuracy
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value: 39.07
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- name: 25-shot
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type: accuracy
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value: 39.67
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_mmlu
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type: OpenLLM-Ro/ro_mmlu
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metrics:
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- name: 0-shot
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type: accuracy
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value: 25.82
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- name: 1-shot
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type: accuracy
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value: 25.48
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- name: 3-shot
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type: accuracy
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value: 27.61
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- name: 5-shot
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type: accuracy
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value: 29.96
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_winogrande
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type: OpenLLM-Ro/ro_winogrande
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metrics:
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- name: 0-shot
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type: accuracy
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value: 58.72
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- name: 1-shot
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type: accuracy
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value: 58.88
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- name: 3-shot
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type: accuracy
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value: 60.38
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- name: 5-shot
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type: accuracy
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value: 59.19
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_hellaswag
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type: OpenLLM-Ro/ro_hellaswag
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metrics:
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- name: 0-shot
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type: accuracy
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value: 55.85
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- name: 1-shot
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type: accuracy
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value: 57.06
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- name: 3-shot
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type: accuracy
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value: 57.52
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- name: 5-shot
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type: accuracy
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value: 57.89
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- name: 10-shot
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type: accuracy
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value: 57.79
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- task:
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type: text-generation
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dataset:
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name: OpenLLM-Ro/ro_gsm8k
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type: OpenLLM-Ro/ro_gsm8k
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metrics:
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- name: 0-shot
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type: accuracy
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value: 0
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- name: 1-shot
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type: accuracy
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value: 2.96
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- name: 3-shot
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type: accuracy
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value: 4.62
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- task:
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type: text-generation
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dataset:
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name: LaRoSeDa_binary
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type: LaRoSeDa_binary
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metrics:
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- name: 0-shot
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type: macro-f1
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value: 42.78
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- name: 1-shot
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type: macro-f1
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value: 98
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- name: 3-shot
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type: macro-f1
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value: 95.13
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- name: 5-shot
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type: macro-f1
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value: 97.07
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- task:
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type: text-generation
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dataset:
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name: LaRoSeDa_multiclass
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type: LaRoSeDa_multiclass
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metrics:
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- name: 0-shot
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type: macro-f1
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value: 46.41
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- name: 1-shot
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type: macro-f1
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-
value: 67.36
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- name: 3-shot
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type: macro-f1
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value: 65.16
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- name: 5-shot
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type: macro-f1
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value: 65.23
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- task:
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type: text-generation
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dataset:
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name: WMT_EN-RO
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type: WMT_EN-RO
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metrics:
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| 354 |
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- name: 0-shot
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| 355 |
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type: bleu
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-
value: 4.45
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| 357 |
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- name: 1-shot
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| 358 |
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type: bleu
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| 359 |
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value: 8.61
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| 360 |
-
- name: 3-shot
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| 361 |
-
type: bleu
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| 362 |
-
value: 12.25
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| 363 |
-
- name: 5-shot
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| 364 |
-
type: bleu
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| 365 |
-
value: 14.73
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-
- task:
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-
type: text-generation
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dataset:
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name: WMT_RO-EN
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type: WMT_RO-EN
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metrics:
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| 372 |
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- name: 0-shot
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| 373 |
-
type: bleu
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| 374 |
-
value: 1.29
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| 375 |
-
- name: 1-shot
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-
type: bleu
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| 377 |
-
value: 10.78
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-
- name: 3-shot
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-
type: bleu
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| 380 |
-
value: 16.82
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| 381 |
-
- name: 5-shot
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| 382 |
-
type: bleu
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| 383 |
-
value: 23.24
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-
- task:
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type: text-generation
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dataset:
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name: XQuAD_EM
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type: XQuAD_EM
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metrics:
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- name: 0-shot
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-
type: exact_match
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-
value: 5.29
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| 393 |
-
- name: 1-shot
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-
type: exact_match
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| 395 |
-
value: 33.95
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- name: 3-shot
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type: exact_match
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-
value: 39.24
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- name: 5-shot
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type: exact_match
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-
value: 42.1
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- task:
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type: text-generation
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dataset:
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name: XQuAD_F1
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type: XQuAD_F1
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metrics:
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- name: 0-shot
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type: f1
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-
value: 16.17
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- name: 1-shot
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type: f1
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value: 51.84
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- name: 3-shot
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type: f1
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value: 58.82
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- name: 5-shot
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type: f1
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value: 61.29
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- task:
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type: text-generation
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dataset:
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name: STS
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type: STS
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metrics:
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- name: 0-shot
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type: spearman
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-
value: -1.74
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- name: 1-shot
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type: spearman
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value: 15.47
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- name: 3-shot
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type: spearman
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| 434 |
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value: 9.93
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-
- task:
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type: text-generation
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dataset:
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name: STS
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type: STS
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metrics:
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| 441 |
-
- name: 0-shot
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| 442 |
-
type: pearson
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| 443 |
-
value: -1.4
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| 444 |
-
- name: 1-shot
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| 445 |
-
type: pearson
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| 446 |
-
value: 15
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| 447 |
-
- name: 3-shot
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| 448 |
-
type: pearson
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| 449 |
-
value: 10.33
|
| 450 |
datasets:
|
| 451 |
- uonlp/CulturaX
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| 452 |
---
|
| 453 |
|
| 454 |
# Model Card for Model ID
|
|
|
|
| 3 |
language:
|
| 4 |
- ro
|
| 5 |
base_model: meta-llama/Llama-2-7b-hf
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| 6 |
datasets:
|
| 7 |
- uonlp/CulturaX
|
| 8 |
+
model-index:
|
| 9 |
+
- name: OpenLLM-Ro/RoLlama2-7b-Base-2024-05-14
|
| 10 |
+
results:
|
| 11 |
+
- task:
|
| 12 |
+
type: text-generation
|
| 13 |
+
dataset:
|
| 14 |
+
name: Romanian_Academic_Benchmarks
|
| 15 |
+
type: Romanian_Academic_Benchmarks
|
| 16 |
+
metrics:
|
| 17 |
+
- name: Average accuracy
|
| 18 |
+
type: accuracy
|
| 19 |
+
value: 38.03
|
| 20 |
+
- task:
|
| 21 |
+
type: text-generation
|
| 22 |
+
dataset:
|
| 23 |
+
name: OpenLLM-Ro/ro_arc_challenge
|
| 24 |
+
type: OpenLLM-Ro/ro_arc_challenge
|
| 25 |
+
metrics:
|
| 26 |
+
- name: Average accuracy
|
| 27 |
+
type: accuracy
|
| 28 |
+
value: 37.95
|
| 29 |
+
- task:
|
| 30 |
+
type: text-generation
|
| 31 |
+
dataset:
|
| 32 |
+
name: OpenLLM-Ro/ro_mmlu
|
| 33 |
+
type: OpenLLM-Ro/ro_mmlu
|
| 34 |
+
metrics:
|
| 35 |
+
- name: Average accuracy
|
| 36 |
+
type: accuracy
|
| 37 |
+
value: 27.22
|
| 38 |
+
- task:
|
| 39 |
+
type: text-generation
|
| 40 |
+
dataset:
|
| 41 |
+
name: OpenLLM-Ro/ro_winogrande
|
| 42 |
+
type: OpenLLM-Ro/ro_winogrande
|
| 43 |
+
metrics:
|
| 44 |
+
- name: Average accuracy
|
| 45 |
+
type: accuracy
|
| 46 |
+
value: 59.29
|
| 47 |
+
- task:
|
| 48 |
+
type: text-generation
|
| 49 |
+
dataset:
|
| 50 |
+
name: OpenLLM-Ro/ro_hellaswag
|
| 51 |
+
type: OpenLLM-Ro/ro_hellaswag
|
| 52 |
+
metrics:
|
| 53 |
+
- name: Average accuracy
|
| 54 |
+
type: accuracy
|
| 55 |
+
value: 57.22
|
| 56 |
+
- task:
|
| 57 |
+
type: text-generation
|
| 58 |
+
dataset:
|
| 59 |
+
name: OpenLLM-Ro/ro_gsm8k
|
| 60 |
+
type: OpenLLM-Ro/ro_gsm8k
|
| 61 |
+
metrics:
|
| 62 |
+
- name: Average accuracy
|
| 63 |
+
type: accuracy
|
| 64 |
+
value: 2.53
|
| 65 |
+
- task:
|
| 66 |
+
type: text-generation
|
| 67 |
+
dataset:
|
| 68 |
+
name: OpenLLM-Ro/ro_truthfulqa
|
| 69 |
+
type: OpenLLM-Ro/ro_truthfulqa
|
| 70 |
+
metrics:
|
| 71 |
+
- name: Average accuracy
|
| 72 |
+
type: accuracy
|
| 73 |
+
value: 44.00
|
| 74 |
+
- task:
|
| 75 |
+
type: text-generation
|
| 76 |
+
dataset:
|
| 77 |
+
name: LaRoSeDa_binary
|
| 78 |
+
type: LaRoSeDa_binary
|
| 79 |
+
metrics:
|
| 80 |
+
- name: Average macro-f1
|
| 81 |
+
type: macro-f1
|
| 82 |
+
value: 83.25
|
| 83 |
+
- task:
|
| 84 |
+
type: text-generation
|
| 85 |
+
dataset:
|
| 86 |
+
name: LaRoSeDa_multiclass
|
| 87 |
+
type: LaRoSeDa_multiclass
|
| 88 |
+
metrics:
|
| 89 |
+
- name: Average macro-f1
|
| 90 |
+
type: macro-f1
|
| 91 |
+
value: 61.04
|
| 92 |
+
- task:
|
| 93 |
+
type: text-generation
|
| 94 |
+
dataset:
|
| 95 |
+
name: LaRoSeDa_binary_finetuned
|
| 96 |
+
type: LaRoSeDa_binary_finetuned
|
| 97 |
+
metrics:
|
| 98 |
+
- name: Average macro-f1
|
| 99 |
+
type: macro-f1
|
| 100 |
+
value: 98.97
|
| 101 |
+
- task:
|
| 102 |
+
type: text-generation
|
| 103 |
+
dataset:
|
| 104 |
+
name: LaRoSeDa_multiclass_finetuned
|
| 105 |
+
type: LaRoSeDa_multiclass_finetuned
|
| 106 |
+
metrics:
|
| 107 |
+
- name: Average macro-f1
|
| 108 |
+
type: macro-f1
|
| 109 |
+
value: 87.72
|
| 110 |
+
- task:
|
| 111 |
+
type: text-generation
|
| 112 |
+
dataset:
|
| 113 |
+
name: WMT_EN-RO
|
| 114 |
+
type: WMT_EN-RO
|
| 115 |
+
metrics:
|
| 116 |
+
- name: Average bleu
|
| 117 |
+
type: bleu
|
| 118 |
+
value: 10.01
|
| 119 |
+
- task:
|
| 120 |
+
type: text-generation
|
| 121 |
+
dataset:
|
| 122 |
+
name: WMT_RO-EN
|
| 123 |
+
type: WMT_RO-EN
|
| 124 |
+
metrics:
|
| 125 |
+
- name: Average bleu
|
| 126 |
+
type: bleu
|
| 127 |
+
value: 13.03
|
| 128 |
+
- task:
|
| 129 |
+
type: text-generation
|
| 130 |
+
dataset:
|
| 131 |
+
name: WMT_EN-RO_finetuned
|
| 132 |
+
type: WMT_EN-RO_finetuned
|
| 133 |
+
metrics:
|
| 134 |
+
- name: Average bleu
|
| 135 |
+
type: bleu
|
| 136 |
+
value: 27.85
|
| 137 |
+
- task:
|
| 138 |
+
type: text-generation
|
| 139 |
+
dataset:
|
| 140 |
+
name: WMT_RO-EN_finetuned
|
| 141 |
+
type: WMT_RO-EN_finetuned
|
| 142 |
+
metrics:
|
| 143 |
+
- name: Average bleu
|
| 144 |
+
type: bleu
|
| 145 |
+
value: 39.30
|
| 146 |
+
- task:
|
| 147 |
+
type: text-generation
|
| 148 |
+
dataset:
|
| 149 |
+
name: XQuAD
|
| 150 |
+
type: XQuAD
|
| 151 |
+
metrics:
|
| 152 |
+
- name: Average exact_match
|
| 153 |
+
type: exact_match
|
| 154 |
+
value: 30.15
|
| 155 |
+
- task:
|
| 156 |
+
type: text-generation
|
| 157 |
+
dataset:
|
| 158 |
+
name: XQuAD
|
| 159 |
+
type: XQuAD
|
| 160 |
+
metrics:
|
| 161 |
+
- name: Average f1
|
| 162 |
+
type: f1
|
| 163 |
+
value: 47.03
|
| 164 |
+
- task:
|
| 165 |
+
type: text-generation
|
| 166 |
+
dataset:
|
| 167 |
+
name: XQuAD_finetuned
|
| 168 |
+
type: XQuAD_finetuned
|
| 169 |
+
metrics:
|
| 170 |
+
- name: Average exact_match
|
| 171 |
+
type: exact_match
|
| 172 |
+
value: 67.06
|
| 173 |
+
- task:
|
| 174 |
+
type: text-generation
|
| 175 |
+
dataset:
|
| 176 |
+
name: XQuAD_finetuned
|
| 177 |
+
type: XQuAD_finetuned
|
| 178 |
+
metrics:
|
| 179 |
+
- name: Average f1
|
| 180 |
+
type: f1
|
| 181 |
+
value: 79.96
|
| 182 |
+
- task:
|
| 183 |
+
type: text-generation
|
| 184 |
+
dataset:
|
| 185 |
+
name: STS
|
| 186 |
+
type: STS
|
| 187 |
+
metrics:
|
| 188 |
+
- name: Average spearman
|
| 189 |
+
type: spearman
|
| 190 |
+
value: 7.89
|
| 191 |
+
- task:
|
| 192 |
+
type: text-generation
|
| 193 |
+
dataset:
|
| 194 |
+
name: STS
|
| 195 |
+
type: STS
|
| 196 |
+
metrics:
|
| 197 |
+
- name: Average pearson
|
| 198 |
+
type: pearson
|
| 199 |
+
value: 7.98
|
| 200 |
+
- task:
|
| 201 |
+
type: text-generation
|
| 202 |
+
dataset:
|
| 203 |
+
name: STS_finetuned
|
| 204 |
+
type: STS_finetuned
|
| 205 |
+
metrics:
|
| 206 |
+
- name: Average spearman
|
| 207 |
+
type: spearman
|
| 208 |
+
value: 71.75
|
| 209 |
+
- task:
|
| 210 |
+
type: text-generation
|
| 211 |
+
dataset:
|
| 212 |
+
name: STS_finetuned
|
| 213 |
+
type: STS_finetuned
|
| 214 |
+
metrics:
|
| 215 |
+
- name: Average pearson
|
| 216 |
+
type: pearson
|
| 217 |
+
value: 71.99
|
| 218 |
+
- task:
|
| 219 |
+
type: text-generation
|
| 220 |
+
dataset:
|
| 221 |
+
name: OpenLLM-Ro/ro_arc_challenge
|
| 222 |
+
type: OpenLLM-Ro/ro_arc_challenge
|
| 223 |
+
metrics:
|
| 224 |
+
- name: 0-shot
|
| 225 |
+
type: accuracy
|
| 226 |
+
value: 35.56
|
| 227 |
+
- name: 1-shot
|
| 228 |
+
type: accuracy
|
| 229 |
+
value: 36.42
|
| 230 |
+
- name: 3-shot
|
| 231 |
+
type: accuracy
|
| 232 |
+
value: 38.56
|
| 233 |
+
- name: 5-shot
|
| 234 |
+
type: accuracy
|
| 235 |
+
value: 38.39
|
| 236 |
+
- name: 10-shot
|
| 237 |
+
type: accuracy
|
| 238 |
+
value: 39.07
|
| 239 |
+
- name: 25-shot
|
| 240 |
+
type: accuracy
|
| 241 |
+
value: 39.67
|
| 242 |
+
- task:
|
| 243 |
+
type: text-generation
|
| 244 |
+
dataset:
|
| 245 |
+
name: OpenLLM-Ro/ro_mmlu
|
| 246 |
+
type: OpenLLM-Ro/ro_mmlu
|
| 247 |
+
metrics:
|
| 248 |
+
- name: 0-shot
|
| 249 |
+
type: accuracy
|
| 250 |
+
value: 25.82
|
| 251 |
+
- name: 1-shot
|
| 252 |
+
type: accuracy
|
| 253 |
+
value: 25.48
|
| 254 |
+
- name: 3-shot
|
| 255 |
+
type: accuracy
|
| 256 |
+
value: 27.61
|
| 257 |
+
- name: 5-shot
|
| 258 |
+
type: accuracy
|
| 259 |
+
value: 29.96
|
| 260 |
+
- task:
|
| 261 |
+
type: text-generation
|
| 262 |
+
dataset:
|
| 263 |
+
name: OpenLLM-Ro/ro_winogrande
|
| 264 |
+
type: OpenLLM-Ro/ro_winogrande
|
| 265 |
+
metrics:
|
| 266 |
+
- name: 0-shot
|
| 267 |
+
type: accuracy
|
| 268 |
+
value: 58.72
|
| 269 |
+
- name: 1-shot
|
| 270 |
+
type: accuracy
|
| 271 |
+
value: 58.88
|
| 272 |
+
- name: 3-shot
|
| 273 |
+
type: accuracy
|
| 274 |
+
value: 60.38
|
| 275 |
+
- name: 5-shot
|
| 276 |
+
type: accuracy
|
| 277 |
+
value: 59.19
|
| 278 |
+
- task:
|
| 279 |
+
type: text-generation
|
| 280 |
+
dataset:
|
| 281 |
+
name: OpenLLM-Ro/ro_hellaswag
|
| 282 |
+
type: OpenLLM-Ro/ro_hellaswag
|
| 283 |
+
metrics:
|
| 284 |
+
- name: 0-shot
|
| 285 |
+
type: accuracy
|
| 286 |
+
value: 55.85
|
| 287 |
+
- name: 1-shot
|
| 288 |
+
type: accuracy
|
| 289 |
+
value: 57.06
|
| 290 |
+
- name: 3-shot
|
| 291 |
+
type: accuracy
|
| 292 |
+
value: 57.52
|
| 293 |
+
- name: 5-shot
|
| 294 |
+
type: accuracy
|
| 295 |
+
value: 57.89
|
| 296 |
+
- name: 10-shot
|
| 297 |
+
type: accuracy
|
| 298 |
+
value: 57.79
|
| 299 |
+
- task:
|
| 300 |
+
type: text-generation
|
| 301 |
+
dataset:
|
| 302 |
+
name: OpenLLM-Ro/ro_gsm8k
|
| 303 |
+
type: OpenLLM-Ro/ro_gsm8k
|
| 304 |
+
metrics:
|
| 305 |
+
- name: 0-shot
|
| 306 |
+
type: accuracy
|
| 307 |
+
value: 0.00
|
| 308 |
+
- name: 1-shot
|
| 309 |
+
type: accuracy
|
| 310 |
+
value: 2.96
|
| 311 |
+
- name: 3-shot
|
| 312 |
+
type: accuracy
|
| 313 |
+
value: 4.62
|
| 314 |
+
- task:
|
| 315 |
+
type: text-generation
|
| 316 |
+
dataset:
|
| 317 |
+
name: LaRoSeDa_binary
|
| 318 |
+
type: LaRoSeDa_binary
|
| 319 |
+
metrics:
|
| 320 |
+
- name: 0-shot
|
| 321 |
+
type: macro-f1
|
| 322 |
+
value: 42.78
|
| 323 |
+
- name: 1-shot
|
| 324 |
+
type: macro-f1
|
| 325 |
+
value: 98.00
|
| 326 |
+
- name: 3-shot
|
| 327 |
+
type: macro-f1
|
| 328 |
+
value: 95.13
|
| 329 |
+
- name: 5-shot
|
| 330 |
+
type: macro-f1
|
| 331 |
+
value: 97.07
|
| 332 |
+
- task:
|
| 333 |
+
type: text-generation
|
| 334 |
+
dataset:
|
| 335 |
+
name: LaRoSeDa_multiclass
|
| 336 |
+
type: LaRoSeDa_multiclass
|
| 337 |
+
metrics:
|
| 338 |
+
- name: 0-shot
|
| 339 |
+
type: macro-f1
|
| 340 |
+
value: 46.41
|
| 341 |
+
- name: 1-shot
|
| 342 |
+
type: macro-f1
|
| 343 |
+
value: 67.36
|
| 344 |
+
- name: 3-shot
|
| 345 |
+
type: macro-f1
|
| 346 |
+
value: 65.16
|
| 347 |
+
- name: 5-shot
|
| 348 |
+
type: macro-f1
|
| 349 |
+
value: 65.23
|
| 350 |
+
- task:
|
| 351 |
+
type: text-generation
|
| 352 |
+
dataset:
|
| 353 |
+
name: WMT_EN-RO
|
| 354 |
+
type: WMT_EN-RO
|
| 355 |
+
metrics:
|
| 356 |
+
- name: 0-shot
|
| 357 |
+
type: bleu
|
| 358 |
+
value: 4.45
|
| 359 |
+
- name: 1-shot
|
| 360 |
+
type: bleu
|
| 361 |
+
value: 8.61
|
| 362 |
+
- name: 3-shot
|
| 363 |
+
type: bleu
|
| 364 |
+
value: 12.25
|
| 365 |
+
- name: 5-shot
|
| 366 |
+
type: bleu
|
| 367 |
+
value: 14.73
|
| 368 |
+
- task:
|
| 369 |
+
type: text-generation
|
| 370 |
+
dataset:
|
| 371 |
+
name: WMT_RO-EN
|
| 372 |
+
type: WMT_RO-EN
|
| 373 |
+
metrics:
|
| 374 |
+
- name: 0-shot
|
| 375 |
+
type: bleu
|
| 376 |
+
value: 1.29
|
| 377 |
+
- name: 1-shot
|
| 378 |
+
type: bleu
|
| 379 |
+
value: 10.78
|
| 380 |
+
- name: 3-shot
|
| 381 |
+
type: bleu
|
| 382 |
+
value: 16.82
|
| 383 |
+
- name: 5-shot
|
| 384 |
+
type: bleu
|
| 385 |
+
value: 23.24
|
| 386 |
+
- task:
|
| 387 |
+
type: text-generation
|
| 388 |
+
dataset:
|
| 389 |
+
name: XQuAD_EM
|
| 390 |
+
type: XQuAD_EM
|
| 391 |
+
metrics:
|
| 392 |
+
- name: 0-shot
|
| 393 |
+
type: exact_match
|
| 394 |
+
value: 5.29
|
| 395 |
+
- name: 1-shot
|
| 396 |
+
type: exact_match
|
| 397 |
+
value: 33.95
|
| 398 |
+
- name: 3-shot
|
| 399 |
+
type: exact_match
|
| 400 |
+
value: 39.24
|
| 401 |
+
- name: 5-shot
|
| 402 |
+
type: exact_match
|
| 403 |
+
value: 42.10
|
| 404 |
+
- task:
|
| 405 |
+
type: text-generation
|
| 406 |
+
dataset:
|
| 407 |
+
name: XQuAD_F1
|
| 408 |
+
type: XQuAD_F1
|
| 409 |
+
metrics:
|
| 410 |
+
- name: 0-shot
|
| 411 |
+
type: f1
|
| 412 |
+
value: 16.17
|
| 413 |
+
- name: 1-shot
|
| 414 |
+
type: f1
|
| 415 |
+
value: 51.84
|
| 416 |
+
- name: 3-shot
|
| 417 |
+
type: f1
|
| 418 |
+
value: 58.82
|
| 419 |
+
- name: 5-shot
|
| 420 |
+
type: f1
|
| 421 |
+
value: 61.29
|
| 422 |
+
- task:
|
| 423 |
+
type: text-generation
|
| 424 |
+
dataset:
|
| 425 |
+
name: STS_Spearman
|
| 426 |
+
type: STS_Spearman
|
| 427 |
+
metrics:
|
| 428 |
+
- name: 1-shot
|
| 429 |
+
type: spearman
|
| 430 |
+
value: -1.74
|
| 431 |
+
- name: 3-shot
|
| 432 |
+
type: spearman
|
| 433 |
+
value: 15.47
|
| 434 |
+
- name: 5-shot
|
| 435 |
+
type: spearman
|
| 436 |
+
value: 9.93
|
| 437 |
+
- task:
|
| 438 |
+
type: text-generation
|
| 439 |
+
dataset:
|
| 440 |
+
name: STS_Pearson
|
| 441 |
+
type: STS_Pearson
|
| 442 |
+
metrics:
|
| 443 |
+
- name: 1-shot
|
| 444 |
+
type: pearson
|
| 445 |
+
value: -1.40
|
| 446 |
+
- name: 3-shot
|
| 447 |
+
type: pearson
|
| 448 |
+
value: 15.00
|
| 449 |
+
- name: 5-shot
|
| 450 |
+
type: pearson
|
| 451 |
+
value: 10.33
|
| 452 |
+
|
| 453 |
---
|
| 454 |
|
| 455 |
# Model Card for Model ID
|