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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: finetune_add_transformer |
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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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# finetune_add_transformer |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2934 |
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- Cer: 0.0724 |
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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: 3e-05 |
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- train_batch_size: 8 |
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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: 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: 2000 |
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- training_steps: 10000 |
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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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| 4.2464 | 5.95 | 500 | 0.7569 | 0.2284 | |
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| 0.5463 | 11.9 | 1000 | 0.3276 | 0.0814 | |
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| 0.3545 | 17.86 | 1500 | 0.3084 | 0.0779 | |
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| 0.2841 | 23.81 | 2000 | 0.3200 | 0.0756 | |
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| 0.232 | 29.76 | 2500 | 0.3181 | 0.0735 | |
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| 0.1922 | 35.71 | 3000 | 0.3480 | 0.0731 | |
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| 0.1601 | 41.67 | 3500 | 0.3990 | 0.0742 | |
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| 0.1362 | 47.62 | 4000 | 0.4304 | 0.0736 | |
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| 0.1165 | 53.57 | 4500 | 0.4847 | 0.0746 | |
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| 0.0994 | 59.52 | 5000 | 0.5250 | 0.0761 | |
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| 0.0876 | 65.48 | 5500 | 0.5628 | 0.0740 | |
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| 0.0791 | 71.43 | 6000 | 0.5871 | 0.0742 | |
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| 0.0716 | 77.38 | 6500 | 0.5933 | 0.0729 | |
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| 0.0661 | 83.33 | 7000 | 0.6238 | 0.0739 | |
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| 0.0605 | 89.29 | 7500 | 0.6623 | 0.0742 | |
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| 0.0569 | 95.24 | 8000 | 0.6638 | 0.0729 | |
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| 0.0535 | 101.19 | 8500 | 0.6681 | 0.0730 | |
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| 0.0498 | 107.14 | 9000 | 0.6815 | 0.0733 | |
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| 0.0491 | 113.1 | 9500 | 0.6818 | 0.0733 | |
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| 0.0471 | 119.05 | 10000 | 0.6810 | 0.0732 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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