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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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base_model: facebook/wav2vec2-xls-r-300m |
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model-index: |
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- name: wav2vec2-xls-r-300m_phone-mfa_english |
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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-xls-r-300m_phone-mfa_english |
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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: 0.0777 |
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- Per: 0.0169 |
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- Learning Rate: 0.0 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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_ratio: 0.2 |
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- num_epochs: 10 |
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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 | Per | Rate | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 5.9243 | 1.0 | 892 | 2.9797 | 0.8601 | 5e-05 | |
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| 0.7497 | 2.0 | 1784 | 0.1314 | 0.0288 | 0.0001 | |
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| 0.2391 | 3.0 | 2676 | 0.0994 | 0.0229 | 0.0001 | |
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| 0.1839 | 4.0 | 3568 | 0.0905 | 0.0211 | 0.0001 | |
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| 0.1562 | 5.0 | 4460 | 0.0879 | 0.0197 | 0.0001 | |
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| 0.14 | 6.0 | 5352 | 0.0872 | 0.0186 | 5e-05 | |
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| 0.1256 | 7.0 | 6244 | 0.0827 | 0.0178 | 0.0000 | |
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| 0.1149 | 8.0 | 7136 | 0.0774 | 0.0173 | 0.0000 | |
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| 0.1083 | 9.0 | 8028 | 0.0786 | 0.0170 | 0.0000 | |
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| 0.1027 | 10.0 | 8920 | 0.0777 | 0.0169 | 0.0 | |
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### Framework versions |
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- Transformers 4.37.1 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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