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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_at0.8_da0.1 |
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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_at0.8_da0.1 |
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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: 4.7430 |
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- Wer: 0.8847 |
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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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| 32.6282 | 50.0 | 250 | 4.0044 | 1.0 | |
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| 3.5474 | 100.0 | 500 | 3.1597 | 1.0 | |
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| 3.0565 | 150.0 | 750 | 3.0680 | 1.0 | |
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| 2.8909 | 200.0 | 1000 | 3.0005 | 1.0 | |
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| 2.292 | 250.0 | 1250 | 2.6442 | 0.9991 | |
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| 1.2329 | 300.0 | 1500 | 2.9696 | 0.9577 | |
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| 0.6684 | 350.0 | 1750 | 3.4034 | 0.9453 | |
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| 0.4377 | 400.0 | 2000 | 3.7834 | 0.9389 | |
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| 0.3292 | 450.0 | 2250 | 3.9480 | 0.9000 | |
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| 0.2554 | 500.0 | 2500 | 4.3241 | 0.8906 | |
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| 0.2073 | 550.0 | 2750 | 4.4139 | 0.9047 | |
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| 0.1762 | 600.0 | 3000 | 4.5423 | 0.9000 | |
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| 0.1551 | 650.0 | 3250 | 4.5978 | 0.8817 | |
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| 0.1403 | 700.0 | 3500 | 4.6304 | 0.8757 | |
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| 0.1286 | 750.0 | 3750 | 4.6839 | 0.8855 | |
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| 0.1201 | 800.0 | 4000 | 4.7430 | 0.8847 | |
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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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