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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_at0.7_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_at0.7_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: 1.8380 |
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- Wer: 0.1653 |
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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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| 18.7456 | 4.46 | 250 | 4.0623 | 1.0 | |
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| 3.321 | 8.93 | 500 | 3.1987 | 1.0 | |
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| 3.0779 | 13.39 | 750 | 3.0954 | 1.0 | |
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| 1.8257 | 17.86 | 1000 | 0.8216 | 0.6275 | |
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| 0.3449 | 22.32 | 1250 | 1.1757 | 0.3268 | |
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| 0.2036 | 26.79 | 1500 | 1.2369 | 0.1982 | |
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| 0.1299 | 31.25 | 1750 | 1.1629 | 0.1991 | |
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| 0.0998 | 35.71 | 2000 | 1.3491 | 0.1743 | |
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| 0.0772 | 40.18 | 2250 | 1.4032 | 0.1730 | |
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| 0.0667 | 44.64 | 2500 | 1.7240 | 0.1756 | |
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| 0.0558 | 49.11 | 2750 | 1.7005 | 0.1709 | |
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| 0.0488 | 53.57 | 3000 | 1.7088 | 0.1717 | |
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| 0.0427 | 58.04 | 3250 | 1.6884 | 0.1649 | |
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| 0.0389 | 62.5 | 3500 | 1.7467 | 0.1670 | |
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| 0.035 | 66.96 | 3750 | 1.8174 | 0.1653 | |
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| 0.0332 | 71.43 | 4000 | 1.8380 | 0.1653 | |
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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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