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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-300m |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-E10_speed2 |
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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-E10_speed2 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.3504 |
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- Cer: 92.7732 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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| 57.6816 | 0.1289 | 200 | 6.9208 | 100.0 | |
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| 30.0241 | 0.2579 | 400 | 4.9760 | 99.2186 | |
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| 25.7956 | 0.3868 | 600 | 5.0354 | 93.9248 | |
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| 26.9553 | 0.5158 | 800 | 4.7842 | 94.0834 | |
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| 10.9188 | 0.6447 | 1000 | 5.0386 | 93.0141 | |
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| 4.8381 | 0.7737 | 1200 | 4.8832 | 93.1669 | |
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| 5.8977 | 0.9026 | 1400 | 4.7683 | 93.9953 | |
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| 5.9801 | 1.0316 | 1600 | 4.4577 | 94.1011 | |
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| 4.624 | 1.1605 | 1800 | 4.4622 | 93.7720 | |
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| 4.5279 | 1.2895 | 2000 | 4.4747 | 93.8132 | |
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| 4.5665 | 1.4184 | 2200 | 4.4467 | 93.8895 | |
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| 4.5274 | 1.5474 | 2400 | 4.4445 | 94.0541 | |
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| 4.5253 | 1.6763 | 2600 | 4.4448 | 93.8719 | |
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| 4.4933 | 1.8053 | 2800 | 4.4757 | 93.5723 | |
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| 4.4909 | 1.9342 | 3000 | 4.4318 | 93.5781 | |
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| 4.4942 | 2.0632 | 3200 | 4.4363 | 93.0905 | |
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| 4.3985 | 2.1921 | 3400 | 4.4396 | 92.9965 | |
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| 4.3714 | 2.3211 | 3600 | 4.3876 | 92.6263 | |
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| 4.3536 | 2.4500 | 3800 | 4.3960 | 92.9788 | |
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| 4.3598 | 2.5790 | 4000 | 4.3974 | 92.9553 | |
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| 4.3408 | 2.7079 | 4200 | 4.3550 | 92.7497 | |
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| 4.3141 | 2.8369 | 4400 | 4.3579 | 92.9377 | |
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| 4.2794 | 2.9658 | 4600 | 4.3504 | 92.7732 | |
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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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