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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_at0.9_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_at0.9_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: 2.0012 |
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- Wer: 0.1794 |
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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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| 15.834 | 6.1 | 250 | 3.6941 | 1.0 | |
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| 3.1623 | 12.2 | 500 | 3.3447 | 1.0 | |
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| 2.81 | 18.29 | 750 | 1.9439 | 0.9983 | |
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| 0.4575 | 24.39 | 1000 | 1.2543 | 0.2499 | |
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| 0.1302 | 30.49 | 1250 | 1.5064 | 0.2080 | |
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| 0.0852 | 36.59 | 1500 | 1.5567 | 0.1995 | |
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| 0.0618 | 42.68 | 1750 | 1.8019 | 0.1982 | |
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| 0.0497 | 48.78 | 2000 | 1.8515 | 0.2025 | |
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| 0.0395 | 54.88 | 2250 | 1.8758 | 0.1897 | |
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| 0.0301 | 60.98 | 2500 | 1.7991 | 0.1850 | |
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| 0.0275 | 67.07 | 2750 | 1.9686 | 0.1777 | |
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| 0.0213 | 73.17 | 3000 | 1.8964 | 0.1884 | |
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| 0.02 | 79.27 | 3250 | 1.9815 | 0.1854 | |
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| 0.017 | 85.37 | 3500 | 2.0240 | 0.1790 | |
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| 0.0157 | 91.46 | 3750 | 1.9606 | 0.1768 | |
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| 0.0137 | 97.56 | 4000 | 2.0012 | 0.1794 | |
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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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