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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_lr1e-4_at0.8_da0.6 |
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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_lr1e-4_at0.8_da0.6 |
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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: 2.5777 |
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- Wer: 0.1820 |
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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: 0.0001 |
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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: 3500 |
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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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| 15.4716 | 8.93 | 250 | 3.5805 | 1.0 | |
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| 3.156 | 17.86 | 500 | 3.1574 | 1.0 | |
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| 2.6095 | 26.79 | 750 | 1.2490 | 1.0 | |
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| 0.2716 | 35.71 | 1000 | 1.6097 | 0.2422 | |
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| 0.0901 | 44.64 | 1250 | 1.8537 | 0.2085 | |
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| 0.0526 | 53.57 | 1500 | 1.7249 | 0.2080 | |
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| 0.0328 | 62.5 | 1750 | 2.2934 | 0.1922 | |
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| 0.0237 | 71.43 | 2000 | 2.1689 | 0.1948 | |
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| 0.018 | 80.36 | 2250 | 2.4606 | 0.1918 | |
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| 0.0144 | 89.29 | 2500 | 2.6943 | 0.1837 | |
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| 0.0108 | 98.21 | 2750 | 2.5514 | 0.1807 | |
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| 0.0078 | 107.14 | 3000 | 2.5035 | 0.1858 | |
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| 0.0064 | 116.07 | 3250 | 2.6022 | 0.1845 | |
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| 0.0069 | 125.0 | 3500 | 2.5777 | 0.1820 | |
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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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