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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-1b |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-1b-E3 |
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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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# wav2vec2-1b-E3 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4214 |
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- Cer: 11.5484 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 3 |
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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 | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:-------:| |
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| 10.9096 | 0.2580 | 200 | 4.4784 | 97.7502 | |
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| 2.5397 | 0.5160 | 400 | 1.5540 | 34.0754 | |
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| 1.2018 | 0.7741 | 600 | 1.1079 | 26.2805 | |
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| 0.9714 | 1.0321 | 800 | 0.8312 | 20.3360 | |
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| 0.7789 | 1.2901 | 1000 | 0.7358 | 18.0980 | |
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| 0.6942 | 1.5481 | 1200 | 0.6558 | 17.2580 | |
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| 0.6176 | 1.8062 | 1400 | 0.5847 | 15.0787 | |
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| 0.5476 | 2.0642 | 1600 | 0.5941 | 15.8365 | |
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| 0.4525 | 2.3222 | 1800 | 0.5006 | 13.3870 | |
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| 0.4068 | 2.5802 | 2000 | 0.4577 | 12.6527 | |
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| 0.37 | 2.8383 | 2200 | 0.4214 | 11.5484 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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