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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-Odia-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-Odia-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: 0.2083 |
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- Wer: 0.1897 |
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- Cer: 0.0476 |
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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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| 6.9058 | 2.3622 | 300 | 3.1227 | 1.0 | 0.8690 | |
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| 1.1432 | 4.7244 | 600 | 0.4002 | 0.4333 | 0.1134 | |
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| 0.2628 | 7.0866 | 900 | 0.3145 | 0.3314 | 0.0850 | |
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| 0.1368 | 9.4488 | 1200 | 0.2585 | 0.2716 | 0.0686 | |
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| 0.0865 | 11.8110 | 1500 | 0.2332 | 0.2524 | 0.0619 | |
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| 0.0596 | 14.1732 | 1800 | 0.2253 | 0.2196 | 0.0538 | |
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| 0.0445 | 16.5354 | 2100 | 0.2202 | 0.2100 | 0.0527 | |
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| 0.0324 | 18.8976 | 2400 | 0.2126 | 0.2001 | 0.0511 | |
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| 0.0264 | 21.2598 | 2700 | 0.2089 | 0.1966 | 0.0498 | |
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| 0.0211 | 23.6220 | 3000 | 0.2083 | 0.1897 | 0.0476 | |
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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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