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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: wac2vec-lllfantomlll |
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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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# wac2vec-lllfantomlll |
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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: 0.5560 |
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- Wer: 0.3417 |
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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: 8 |
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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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| 3.5768 | 1.0 | 500 | 2.0283 | 1.0238 | |
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| 0.9219 | 2.01 | 1000 | 0.5103 | 0.5022 | |
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| 0.4497 | 3.01 | 1500 | 0.4746 | 0.4669 | |
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| 0.3163 | 4.02 | 2000 | 0.4144 | 0.4229 | |
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| 0.2374 | 5.02 | 2500 | 0.4186 | 0.4161 | |
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| 0.2033 | 6.02 | 3000 | 0.4115 | 0.3975 | |
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| 0.1603 | 7.03 | 3500 | 0.4424 | 0.3817 | |
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| 0.1455 | 8.03 | 4000 | 0.4151 | 0.3918 | |
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| 0.1276 | 9.04 | 4500 | 0.4940 | 0.3798 | |
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| 0.108 | 10.04 | 5000 | 0.4580 | 0.3688 | |
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| 0.1053 | 11.04 | 5500 | 0.4243 | 0.3700 | |
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| 0.0929 | 12.05 | 6000 | 0.4999 | 0.3727 | |
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| 0.0896 | 13.05 | 6500 | 0.4991 | 0.3624 | |
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| 0.0748 | 14.06 | 7000 | 0.4924 | 0.3602 | |
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| 0.0681 | 15.06 | 7500 | 0.4908 | 0.3544 | |
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| 0.0619 | 16.06 | 8000 | 0.5021 | 0.3559 | |
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| 0.0569 | 17.07 | 8500 | 0.5448 | 0.3518 | |
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| 0.0549 | 18.07 | 9000 | 0.4919 | 0.3508 | |
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| 0.0478 | 19.08 | 9500 | 0.4704 | 0.3513 | |
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| 0.0437 | 20.08 | 10000 | 0.5058 | 0.3555 | |
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| 0.0421 | 21.08 | 10500 | 0.5127 | 0.3489 | |
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| 0.0362 | 22.09 | 11000 | 0.5439 | 0.3527 | |
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| 0.0322 | 23.09 | 11500 | 0.5418 | 0.3469 | |
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| 0.0327 | 24.1 | 12000 | 0.5298 | 0.3422 | |
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| 0.0292 | 25.1 | 12500 | 0.5511 | 0.3426 | |
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| 0.0246 | 26.1 | 13000 | 0.5349 | 0.3472 | |
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| 0.0251 | 27.11 | 13500 | 0.5646 | 0.3391 | |
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| 0.0214 | 28.11 | 14000 | 0.5821 | 0.3424 | |
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| 0.0217 | 29.12 | 14500 | 0.5560 | 0.3417 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 1.18.3 |
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- Tokenizers 0.12.1 |
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