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README.md
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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-google-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-google-colab
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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: 0.5430
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- Wer: 0.3434
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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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| 3.5342 | 1.0 | 500 | 1.7432 | 1.0005 |
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| 0.852 | 2.01 | 1000 | 0.6003 | 0.5692 |
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| 0.4306 | 3.01 | 1500 | 0.4681 | 0.4750 |
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| 0.2972 | 4.02 | 2000 | 0.4397 | 0.4192 |
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| 0.2262 | 5.02 | 2500 | 0.4120 | 0.3985 |
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| 0.1902 | 6.02 | 3000 | 0.4680 | 0.3988 |
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| 0.1664 | 7.03 | 3500 | 0.4740 | 0.4022 |
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| 0.1398 | 8.03 | 4000 | 0.4200 | 0.3788 |
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| 0.1237 | 9.04 | 4500 | 0.4645 | 0.3827 |
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| 0.1087 | 10.04 | 5000 | 0.4520 | 0.3805 |
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| 0.0961 | 11.04 | 5500 | 0.4862 | 0.3712 |
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| 0.0844 | 12.05 | 6000 | 0.4768 | 0.3695 |
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| 0.0808 | 13.05 | 6500 | 0.5238 | 0.3720 |
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| 0.0708 | 14.06 | 7000 | 0.5249 | 0.3736 |
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| 0.0649 | 15.06 | 7500 | 0.5245 | 0.3745 |
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| 0.0639 | 16.06 | 8000 | 0.5152 | 0.3648 |
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| 0.0553 | 17.07 | 8500 | 0.5048 | 0.3682 |
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| 0.0556 | 18.07 | 9000 | 0.5316 | 0.3634 |
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| 0.0469 | 19.08 | 9500 | 0.5179 | 0.3668 |
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| 0.0432 | 20.08 | 10000 | 0.5441 | 0.3679 |
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| 0.0402 | 21.08 | 10500 | 0.5362 | 0.3498 |
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| 0.0344 | 22.09 | 11000 | 0.5497 | 0.3537 |
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| 0.0321 | 23.09 | 11500 | 0.5426 | 0.3499 |
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| 0.0311 | 24.1 | 12000 | 0.5637 | 0.3508 |
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| 0.0279 | 25.1 | 12500 | 0.5346 | 0.3491 |
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| 0.025 | 26.1 | 13000 | 0.5310 | 0.3426 |
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| 0.0237 | 27.11 | 13500 | 0.5419 | 0.3444 |
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| 0.0221 | 28.11 | 14000 | 0.5457 | 0.3437 |
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| 0.0214 | 29.12 | 14500 | 0.5430 | 0.3434 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.12.1+cu113
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- Datasets 1.18.3
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- Tokenizers 0.12.1
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