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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-commonvoice-tamil |
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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-commonvoice-tamil |
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This model is a fine-tuned version of [Harveenchadha/vakyansh-wav2vec2-tamil-tam-250](https://huggingface.co/Harveenchadha/vakyansh-wav2vec2-tamil-tam-250) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3415 |
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- Wer: 1.0 |
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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: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 400 |
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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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| 5.384 | 1.69 | 200 | 3.3400 | 1.0 | |
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| 3.3085 | 3.39 | 400 | 3.3609 | 1.0 | |
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| 3.3008 | 5.08 | 600 | 3.3331 | 1.0 | |
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| 3.2852 | 6.78 | 800 | 3.3492 | 1.0 | |
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| 3.2908 | 8.47 | 1000 | 3.3318 | 1.0 | |
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| 3.2865 | 10.17 | 1200 | 3.3501 | 1.0 | |
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| 3.2826 | 11.86 | 1400 | 3.3403 | 1.0 | |
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| 3.2875 | 13.56 | 1600 | 3.3335 | 1.0 | |
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| 3.2899 | 15.25 | 1800 | 3.3311 | 1.0 | |
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| 3.2755 | 16.95 | 2000 | 3.3617 | 1.0 | |
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| 3.2877 | 18.64 | 2200 | 3.3317 | 1.0 | |
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| 3.2854 | 20.34 | 2400 | 3.3560 | 1.0 | |
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| 3.2878 | 22.03 | 2600 | 3.3332 | 1.0 | |
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| 3.2766 | 23.73 | 2800 | 3.3317 | 1.0 | |
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| 3.2943 | 25.42 | 3000 | 3.3737 | 1.0 | |
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| 3.2845 | 27.12 | 3200 | 3.3347 | 1.0 | |
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| 3.2765 | 28.81 | 3400 | 3.3415 | 1.0 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.3 |
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- Tokenizers 0.10.3 |
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