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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: CS337_finetune_wav2vec_base |
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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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# CS337_finetune_wav2vec_base |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9758 |
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- Accuracy: 0.5838 |
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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: 0.0005 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 20 |
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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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| 0.9835 | 0.97 | 28 | 0.9852 | 0.6256 | |
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| 1.0709 | 1.98 | 57 | 0.9559 | 0.6193 | |
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| 2.2881 | 2.99 | 86 | 1.3049 | 0.5203 | |
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| 1.5153 | 4.0 | 115 | 1.7062 | 0.3604 | |
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| 1.5127 | 4.97 | 143 | 1.3469 | 0.4683 | |
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| 1.4081 | 5.98 | 172 | 1.1282 | 0.5063 | |
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| 1.5358 | 6.99 | 201 | 1.1630 | 0.5355 | |
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| 1.4543 | 8.0 | 230 | 1.6172 | 0.3426 | |
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| 1.4626 | 8.97 | 258 | 1.1863 | 0.5241 | |
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| 1.3419 | 9.98 | 287 | 1.3211 | 0.4898 | |
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| 1.2167 | 10.99 | 316 | 1.1622 | 0.5381 | |
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| 1.3479 | 12.0 | 345 | 1.1126 | 0.5355 | |
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| 1.2712 | 12.97 | 373 | 1.1934 | 0.5102 | |
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| 1.3099 | 13.98 | 402 | 1.0652 | 0.5241 | |
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| 1.1829 | 14.99 | 431 | 1.0393 | 0.5241 | |
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| 1.3834 | 16.0 | 460 | 1.0916 | 0.5508 | |
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| 1.1997 | 16.97 | 488 | 1.0677 | 0.5799 | |
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| 1.1304 | 17.98 | 517 | 0.9980 | 0.5863 | |
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| 1.0456 | 18.99 | 546 | 0.9734 | 0.5863 | |
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| 1.0446 | 19.48 | 560 | 0.9758 | 0.5838 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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