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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-base-timit-demo-colab |
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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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# wav2vec2-base-timit-demo-colab |
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This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0280 |
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- Wer: 0.0082 |
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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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- num_epochs: 30 |
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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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| 0.1152 | 1.42 | 500 | 0.0416 | 0.0159 | |
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| 0.0803 | 2.83 | 1000 | 0.0372 | 0.0144 | |
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| 0.0672 | 4.25 | 1500 | 0.0345 | 0.0119 | |
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| 0.0564 | 5.67 | 2000 | 0.0338 | 0.0106 | |
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| 0.0513 | 7.08 | 2500 | 0.0307 | 0.0100 | |
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| 0.0448 | 8.5 | 3000 | 0.0343 | 0.0098 | |
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| 0.0374 | 9.92 | 3500 | 0.0300 | 0.0084 | |
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| 0.0368 | 11.33 | 4000 | 0.0314 | 0.0086 | |
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| 0.0388 | 12.75 | 4500 | 0.0283 | 0.0089 | |
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| 0.0277 | 14.16 | 5000 | 0.0302 | 0.0089 | |
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| 0.0298 | 15.58 | 5500 | 0.0298 | 0.0089 | |
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| 0.0271 | 17.0 | 6000 | 0.0320 | 0.0098 | |
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| 0.024 | 18.41 | 6500 | 0.0286 | 0.0088 | |
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| 0.0236 | 19.83 | 7000 | 0.0284 | 0.0084 | |
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| 0.0238 | 21.25 | 7500 | 0.0290 | 0.0086 | |
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| 0.0227 | 22.66 | 8000 | 0.0284 | 0.0093 | |
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| 0.0198 | 24.08 | 8500 | 0.0280 | 0.0088 | |
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| 0.0225 | 25.5 | 9000 | 0.0281 | 0.0086 | |
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| 0.018 | 26.91 | 9500 | 0.0280 | 0.0082 | |
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| 0.0178 | 28.33 | 10000 | 0.0280 | 0.0082 | |
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| 0.0209 | 29.75 | 10500 | 0.0280 | 0.0082 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
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