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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: output |
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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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# output |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2822 |
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- Wer: 0.2423 |
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- Cer: 0.0842 |
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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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I have used dataset other than mozila common voice, thats why for fair evaluation, i do 80:20 split. |
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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: 0.0003 |
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- train_batch_size: 48 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 192 |
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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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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:------:|:---------------:|:------:| |
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| No log | 1.0 | 174 | 0.9860 | 3.1257 | 1.0 | |
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| No log | 2.0 | 348 | 0.9404 | 2.4914 | 0.9997 | |
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| No log | 3.0 | 522 | 0.1889 | 0.5970 | 0.5376 | |
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| No log | 4.0 | 696 | 0.1428 | 0.4462 | 0.4121 | |
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| No log | 5.0 | 870 | 0.1211 | 0.3775 | 0.3525 | |
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| 1.7 | 6.0 | 1044 | 0.1113 | 0.3594 | 0.3264 | |
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| 1.7 | 7.0 | 1218 | 0.1032 | 0.3354 | 0.3013 | |
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| 1.7 | 8.0 | 1392 | 0.1005 | 0.3171 | 0.2843 | |
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| 1.7 | 9.0 | 1566 | 0.0953 | 0.3115 | 0.2717 | |
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| 1.7 | 10.0 | 1740 | 0.0934 | 0.3058 | 0.2671 | |
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| 1.7 | 11.0 | 1914 | 0.0926 | 0.3060 | 0.2656 | |
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| 0.3585 | 12.0 | 2088 | 0.0899 | 0.3070 | 0.2566 | |
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| 0.3585 | 13.0 | 2262 | 0.0888 | 0.2979 | 0.2509 | |
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| 0.3585 | 14.0 | 2436 | 0.0868 | 0.3005 | 0.2473 | |
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| 0.3585 | 15.0 | 2610 | 0.2822 | 0.2423 | 0.0842 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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