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--- |
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tags: |
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- generated_from_trainer |
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base_model: patrickvonplaten/wav2vec2-xls-r-phoneme-300m-tr |
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model-index: |
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- name: wav2vec2-xls-r-phoneme-300m-tr-ogma-phoneme |
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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-phoneme-300m-tr-ogma-phoneme |
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This model is a fine-tuned version of [patrickvonplaten/wav2vec2-xls-r-phoneme-300m-tr](https://huggingface.co/patrickvonplaten/wav2vec2-xls-r-phoneme-300m-tr) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6886 |
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- Cer: 0.7624 |
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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: 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: 100 |
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- num_epochs: 30 |
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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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| 9.8242 | 1.0 | 17 | 10.2075 | 1.7574 | |
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| 7.5139 | 2.0 | 34 | 6.2677 | 1.8317 | |
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| 4.93 | 3.0 | 51 | 4.4229 | 0.9950 | |
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| 3.787 | 4.0 | 68 | 3.6279 | 0.9604 | |
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| 3.2056 | 5.0 | 85 | 3.3155 | 0.9109 | |
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| 2.8302 | 6.0 | 102 | 3.0498 | 0.8515 | |
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| 2.6059 | 7.0 | 119 | 2.9567 | 0.8366 | |
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| 2.3369 | 8.0 | 136 | 2.8454 | 0.8465 | |
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| 2.0347 | 9.0 | 153 | 2.7595 | 0.8663 | |
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| 1.787 | 10.0 | 170 | 2.8327 | 0.8416 | |
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| 1.5493 | 11.0 | 187 | 2.7142 | 0.8465 | |
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| 1.3992 | 12.0 | 204 | 2.7668 | 0.8713 | |
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| 1.3539 | 13.0 | 221 | 2.7595 | 0.8465 | |
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| 1.1791 | 14.0 | 238 | 2.6278 | 0.8366 | |
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| 1.1649 | 15.0 | 255 | 2.8350 | 0.8564 | |
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| 1.0361 | 16.0 | 272 | 2.7286 | 0.7921 | |
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| 0.9179 | 17.0 | 289 | 2.6409 | 0.7772 | |
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| 0.8338 | 18.0 | 306 | 2.6040 | 0.7574 | |
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| 0.7847 | 19.0 | 323 | 2.7403 | 0.8564 | |
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| 0.82 | 20.0 | 340 | 2.6313 | 0.8168 | |
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| 0.753 | 21.0 | 357 | 2.5469 | 0.8168 | |
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| 0.6124 | 22.0 | 374 | 2.5799 | 0.7822 | |
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| 0.6236 | 23.0 | 391 | 2.6548 | 0.8069 | |
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| 0.5955 | 24.0 | 408 | 2.6331 | 0.8317 | |
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| 0.592 | 25.0 | 425 | 2.6168 | 0.8366 | |
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| 0.5169 | 26.0 | 442 | 2.6168 | 0.8069 | |
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| 0.5012 | 27.0 | 459 | 2.5482 | 0.7723 | |
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| 0.44 | 28.0 | 476 | 2.6088 | 0.8020 | |
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| 0.4243 | 29.0 | 493 | 2.6753 | 0.7871 | |
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| 0.4824 | 30.0 | 510 | 2.6886 | 0.7624 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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