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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: 1.0838 |
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- Wer: 0.1768 |
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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: 500 |
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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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| 16.3345 | 3.91 | 250 | 3.9551 | 1.0 | |
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| 3.2558 | 7.81 | 500 | 3.1516 | 1.0 | |
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| 2.9971 | 11.72 | 750 | 2.4403 | 1.0 | |
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| 0.9923 | 15.62 | 1000 | 0.6040 | 0.4938 | |
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| 0.2971 | 19.53 | 1250 | 0.6870 | 0.2828 | |
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| 0.1765 | 23.44 | 1500 | 0.8956 | 0.2431 | |
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| 0.1185 | 27.34 | 1750 | 0.9472 | 0.2029 | |
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| 0.0919 | 31.25 | 2000 | 1.0306 | 0.1833 | |
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| 0.0692 | 35.16 | 2250 | 0.9844 | 0.1939 | |
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| 0.0577 | 39.06 | 2500 | 1.0122 | 0.1862 | |
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| 0.0467 | 42.97 | 2750 | 1.0849 | 0.1734 | |
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| 0.0407 | 46.88 | 3000 | 0.9989 | 0.1841 | |
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| 0.0341 | 50.78 | 3250 | 1.0820 | 0.1875 | |
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| 0.0299 | 54.69 | 3500 | 1.1344 | 0.1747 | |
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| 0.0291 | 58.59 | 3750 | 1.0495 | 0.1845 | |
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| 0.0247 | 62.5 | 4000 | 1.0838 | 0.1768 | |
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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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