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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-Tamil-large-xlsr53 |
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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-Tamil-large-xlsr53 |
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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: 0.2781 |
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- Wer: 0.3110 |
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- Cer: 0.0517 |
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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: 6 |
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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: 24 |
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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: 500 |
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- training_steps: 3000 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 5.904 | 2.2472 | 300 | 3.1297 | 1.0 | 0.9873 | |
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| 0.9535 | 4.4944 | 600 | 0.3668 | 0.5619 | 0.1031 | |
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| 0.2594 | 6.7416 | 900 | 0.2991 | 0.4758 | 0.0811 | |
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| 0.1648 | 8.9888 | 1200 | 0.2692 | 0.4060 | 0.0670 | |
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| 0.1146 | 11.2360 | 1500 | 0.2712 | 0.3747 | 0.0617 | |
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| 0.0904 | 13.4831 | 1800 | 0.2722 | 0.3488 | 0.0577 | |
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| 0.0734 | 15.7303 | 2100 | 0.2682 | 0.3317 | 0.0568 | |
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| 0.0597 | 17.9775 | 2400 | 0.2778 | 0.3263 | 0.0548 | |
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| 0.0553 | 20.2247 | 2700 | 0.2740 | 0.3153 | 0.0526 | |
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| 0.0466 | 22.4719 | 3000 | 0.2781 | 0.3110 | 0.0517 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 1.18.3 |
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- Tokenizers 0.19.1 |
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