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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
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model-index: |
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- name: TinyLlama-1.1B-SlimOrca-Function-Calling-3T |
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results: |
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- task: |
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type: text-generation |
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metrics: |
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- name: Average |
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type: Average |
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value: 37.38 |
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source: |
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name: Open LLM Leaderboard |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard |
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- task: |
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type: text-generation |
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metrics: |
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- name: ARC |
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type: ARC |
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value: 36.09 |
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source: |
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name: Open LLM Leaderboard |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard |
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- task: |
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type: text-generation |
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metrics: |
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- name: HellaSwag |
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type: HellaSwag |
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value: 59.66 |
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source: |
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name: Open LLM Leaderboard |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard |
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- task: |
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type: text-generation |
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metrics: |
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- name: MMLU |
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type: MMLU |
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value: 28.21 |
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source: |
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name: Open LLM Leaderboard |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard |
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- task: |
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type: text-generation |
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metrics: |
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- name: TruthfulQA |
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type: TruthfulQA |
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value: 36.74 |
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source: |
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name: Open LLM Leaderboard |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard |
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- task: |
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type: text-generation |
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metrics: |
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- name: Winograde |
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type: Winograde |
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value: 59.12 |
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source: |
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name: Open LLM Leaderboard |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard |
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- task: |
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type: text-generation |
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metrics: |
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- name: GSM8K |
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type: GSM8K |
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value: 4.47 |
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source: |
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name: Open LLM Leaderboard |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard |
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datasets: |
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- Open-Orca/SlimOrca-Dedup |
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- gardner/glaive-function-calling-v2-sharegpt |
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language: en |
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--- |
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# TinyLlama-1.1B-SlimOrca-Function-Calling-3T |
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This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the [SlimOrca](https://huggingface.co/datasets/Open-Orca/SlimOrca-Dedup) and [glaive-function-calling-v2](https://huggingface.co/datasets/gardner/glaive-function-calling-v2-sharegpt) datasets. |
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# Evaluation |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7403 |
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Please see the `scripts/llm-eval.py` to recreate the evaluation results from the test split as published here: [gardner/tinyllama-function-calling-eval](https://huggingface.co/datasets/gardner/tinyllama-function-calling-eval). The model responds with function calling when expected and refuses when it doesn't have access to tools. In the linked dataset, `result1` is generated by this model and `result2` is from the test dataset. |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.3.0` |
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```yaml |
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base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
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model_type: LlamaForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_llama_derived_model: true |
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load_in_8bit: true |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: Open-Orca/SlimOrca-Dedup |
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type: sharegpt |
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conversation: chatml |
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- path: gardner/glaive-function-calling-v2-sharegpt |
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type: sharegpt |
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conversation: chatml |
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dataset_prepared_path: ./.prepared-datasets/glaive-function-calling-v2-sharegpt |
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val_set_size: 0.05 |
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output_dir: ./tinyllama/function-calling/chatml |
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sequence_len: 4096 |
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sample_packing: true |
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pad_to_sequence_len: true |
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adapter: lora |
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lora_model_dir: |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 4 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: true |
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fp16: false |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 10 |
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evals_per_epoch: 4 |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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``` |
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</details><br> |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- load_in_8bit: True |
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- load_in_4bit: False |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: fp4 |
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- bnb_4bit_use_double_quant: False |
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- bnb_4bit_compute_dtype: float32 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 1.2492 | 0.0 | 1 | 1.2363 | |
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| 0.7621 | 0.25 | 1896 | 0.8096 | |
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| 0.757 | 0.5 | 3792 | 0.7852 | |
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| 0.6424 | 0.75 | 5688 | 0.7717 | |
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| 0.5944 | 1.04 | 7584 | 0.7625 | |
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| 0.73 | 1.29 | 9480 | 0.7585 | |
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| 0.6781 | 1.54 | 11376 | 0.7521 | |
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| 0.829 | 1.79 | 13272 | 0.7471 | |
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| 0.6964 | 2.08 | 15168 | 0.7467 | |
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| 0.6652 | 2.33 | 17064 | 0.7453 | |
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| 0.7645 | 2.58 | 18960 | 0.7420 | |
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| 0.5702 | 2.83 | 20856 | 0.7392 | |
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| 0.7049 | 3.12 | 22752 | 0.7418 | |
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| 0.6087 | 3.37 | 24648 | 0.7412 | |
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| 0.6064 | 3.62 | 26544 | 0.7405 | |
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| 0.7125 | 3.87 | 28440 | 0.7403 | |
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### Framework versions |
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- PEFT 0.7.0 |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
