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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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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-base-Telugu-large |
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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-Telugu-large |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3811 |
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- Wer: 0.3630 |
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- Cer: 0.0716 |
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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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| 7.205 | 1.9737 | 300 | 3.2285 | 1.0 | 1.0 | |
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| 1.3015 | 3.9474 | 600 | 0.7145 | 0.7256 | 0.1790 | |
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| 0.6733 | 5.9211 | 900 | 0.5099 | 0.6079 | 0.1339 | |
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| 0.5037 | 7.8947 | 1200 | 0.4510 | 0.5383 | 0.1146 | |
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| 0.4039 | 9.8684 | 1500 | 0.3932 | 0.4957 | 0.1011 | |
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| 0.3224 | 11.8421 | 1800 | 0.3733 | 0.4537 | 0.0909 | |
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| 0.2699 | 13.8158 | 2100 | 0.3685 | 0.4291 | 0.0840 | |
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| 0.2177 | 15.7895 | 2400 | 0.3664 | 0.3836 | 0.0747 | |
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| 0.19 | 17.7632 | 2700 | 0.3722 | 0.3821 | 0.0743 | |
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| 0.1596 | 19.7368 | 3000 | 0.3811 | 0.3630 | 0.0716 | |
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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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