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--- |
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language: |
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- ug |
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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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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_11_0 |
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- generated_from_trainer |
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datasets: |
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- common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: xls-r-uyghur-cv11 |
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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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# xls-r-uyghur-cv11 |
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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 MOZILLA-FOUNDATION/COMMON_VOICE_11_0 - UG dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2191 |
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- Wer: 0.3257 |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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- num_epochs: 100.0 |
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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 | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 3.3958 | 4.36 | 500 | 3.3137 | 1.0 | |
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| 3.032 | 8.71 | 1000 | 2.8586 | 0.9993 | |
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| 1.3977 | 13.07 | 1500 | 0.4786 | 0.6375 | |
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| 1.2751 | 17.43 | 2000 | 0.3816 | 0.5393 | |
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| 1.2113 | 21.79 | 2500 | 0.3451 | 0.5099 | |
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| 1.156 | 26.14 | 3000 | 0.3245 | 0.4919 | |
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| 1.1226 | 30.5 | 3500 | 0.2992 | 0.4441 | |
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| 1.0913 | 34.86 | 4000 | 0.2831 | 0.4315 | |
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| 1.0615 | 39.22 | 4500 | 0.2808 | 0.4340 | |
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| 1.0455 | 43.57 | 5000 | 0.2713 | 0.4088 | |
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| 1.0228 | 47.93 | 5500 | 0.2622 | 0.3960 | |
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| 0.9936 | 52.29 | 6000 | 0.2525 | 0.3796 | |
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| 0.968 | 56.64 | 6500 | 0.2506 | 0.3798 | |
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| 0.9704 | 61.0 | 7000 | 0.2481 | 0.3735 | |
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| 0.9552 | 65.36 | 7500 | 0.2394 | 0.3643 | |
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| 0.9417 | 69.72 | 8000 | 0.2350 | 0.3537 | |
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| 0.9215 | 74.07 | 8500 | 0.2326 | 0.3507 | |
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| 0.9097 | 78.43 | 9000 | 0.2277 | 0.3487 | |
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| 0.9003 | 82.79 | 9500 | 0.2230 | 0.3362 | |
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| 0.8857 | 87.15 | 10000 | 0.2246 | 0.3362 | |
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| 0.882 | 91.5 | 10500 | 0.2236 | 0.3315 | |
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| 0.8719 | 95.86 | 11000 | 0.2203 | 0.3271 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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