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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-common-voice-50p-persian-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-common-voice-50p-persian-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: 1.0939 |
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- Wer: 0.6537 |
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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: 7.5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 1 |
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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: 2000 |
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- num_epochs: 40 |
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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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| 3.0437 | 2.52 | 600 | 3.0170 | 1.0 | |
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| 2.3667 | 5.04 | 1200 | 2.1575 | 0.9988 | |
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| 0.9565 | 7.56 | 1800 | 1.0801 | 0.8410 | |
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| 0.603 | 10.08 | 2400 | 0.9680 | 0.7678 | |
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| 0.507 | 12.61 | 3000 | 0.9554 | 0.7470 | |
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| 0.3754 | 15.13 | 3600 | 0.9524 | 0.7157 | |
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| 0.4267 | 17.65 | 4200 | 0.9290 | 0.6980 | |
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| 0.3308 | 20.17 | 4800 | 0.9557 | 0.7061 | |
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| 0.2259 | 22.69 | 5400 | 0.9864 | 0.6830 | |
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| 0.2486 | 25.21 | 6000 | 1.1086 | 0.6812 | |
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| 0.1956 | 27.73 | 6600 | 1.0497 | 0.6805 | |
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| 0.1835 | 30.25 | 7200 | 1.0660 | 0.6596 | |
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| 0.1926 | 32.77 | 7800 | 1.1274 | 0.6600 | |
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| 0.2765 | 35.29 | 8400 | 1.0882 | 0.6603 | |
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| 0.2397 | 37.82 | 9000 | 1.0939 | 0.6537 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 1.18.3 |
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- Tokenizers 0.10.3 |
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