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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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- wer |
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model-index: |
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- name: w2v2-base-pretrained_lr5e-5_at0.0_da1 |
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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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# w2v2-base-pretrained_lr5e-5_at0.0_da1 |
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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: 1.2935 |
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- Wer: 0.1709 |
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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: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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_steps: 1000 |
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- training_steps: 4000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 22.479 | 3.91 | 250 | 4.5097 | 1.0 | |
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| 3.5142 | 7.81 | 500 | 3.2115 | 1.0 | |
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| 3.144 | 11.72 | 750 | 3.1091 | 1.0 | |
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| 2.5815 | 15.62 | 1000 | 1.2241 | 0.9991 | |
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| 0.6479 | 19.53 | 1250 | 0.5868 | 0.3328 | |
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| 0.3255 | 23.44 | 1500 | 0.7123 | 0.2050 | |
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| 0.2136 | 27.34 | 1750 | 0.8753 | 0.1854 | |
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| 0.1561 | 31.25 | 2000 | 0.9095 | 0.1892 | |
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| 0.1195 | 35.16 | 2250 | 1.0824 | 0.1828 | |
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| 0.0966 | 39.06 | 2500 | 1.0976 | 0.1756 | |
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| 0.0829 | 42.97 | 2750 | 1.1946 | 0.1734 | |
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| 0.0724 | 46.88 | 3000 | 1.2161 | 0.1713 | |
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| 0.0611 | 50.78 | 3250 | 1.2877 | 0.1739 | |
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| 0.0555 | 54.69 | 3500 | 1.3169 | 0.1687 | |
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| 0.0537 | 58.59 | 3750 | 1.2744 | 0.1764 | |
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| 0.0481 | 62.5 | 4000 | 1.2935 | 0.1709 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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