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--- |
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license: apache-2.0 |
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base_model: facebook/hubert-base-ls960 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: hubert-base-ls960-finetuned-ic-slurp-no-pretrain |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# hubert-base-ls960-finetuned-ic-slurp-no-pretrain |
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.2153 |
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- Accuracy: 0.2587 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 96 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 3.9001 | 1.0 | 527 | 3.9015 | 0.0736 | |
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| 3.8219 | 2.0 | 1055 | 3.8454 | 0.0766 | |
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| 3.7453 | 3.0 | 1582 | 3.7615 | 0.0837 | |
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| 3.7202 | 4.0 | 2110 | 3.7143 | 0.0912 | |
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| 3.649 | 5.0 | 2637 | 3.6899 | 0.0868 | |
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| 3.6459 | 6.0 | 3165 | 3.6261 | 0.1077 | |
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| 3.5103 | 7.0 | 3692 | 3.5303 | 0.1216 | |
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| 3.4177 | 8.0 | 4220 | 3.4234 | 0.1503 | |
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| 3.3008 | 9.0 | 4747 | 3.3969 | 0.1586 | |
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| 3.0881 | 10.0 | 5275 | 3.2262 | 0.1993 | |
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| 2.9312 | 11.0 | 5802 | 3.1606 | 0.2214 | |
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| 2.7669 | 12.0 | 6330 | 3.1171 | 0.2364 | |
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| 2.5412 | 13.0 | 6857 | 3.1180 | 0.2495 | |
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| 2.4121 | 14.0 | 7385 | 3.1714 | 0.2458 | |
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| 2.1346 | 15.0 | 7912 | 3.2153 | 0.2587 | |
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| 2.0515 | 16.0 | 8440 | 3.3048 | 0.2564 | |
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| 1.7885 | 17.0 | 8967 | 3.3968 | 0.2558 | |
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| 1.6461 | 18.0 | 9495 | 3.5184 | 0.2511 | |
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| 1.4339 | 19.0 | 10022 | 3.7439 | 0.2549 | |
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| 1.2975 | 20.0 | 10550 | 3.8629 | 0.2549 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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