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--- |
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language: |
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- km |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- openslr |
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- robust-speech-event |
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- km |
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- generated_from_trainer |
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model-index: |
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- name: xls-r-300m-km |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: OpenSLR km |
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type: openslr |
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args: km |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 29.26 |
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- name: Test CER |
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type: cer |
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value: 7.93 |
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--- |
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# |
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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 openslr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3142 |
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- Wer: 0.3512 |
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# Evaluation results on OpenSLR "evaluation" (self-split) (Running ./eval.py): |
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- WER: 0.2925882809468374 |
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- CER: 0.0792776460744666 |
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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: 5e-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: 100 |
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- num_epochs: 50 |
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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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| 5.2049 | 4.93 | 400 | 4.5570 | 1.0 | |
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| 3.569 | 9.87 | 800 | 3.5415 | 1.0 | |
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| 3.483 | 14.81 | 1200 | 3.3956 | 1.0 | |
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| 2.1906 | 19.75 | 1600 | 1.1732 | 0.7897 | |
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| 1.7968 | 24.69 | 2000 | 0.7634 | 0.6678 | |
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| 1.615 | 29.62 | 2400 | 0.6182 | 0.5922 | |
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| 1.52 | 34.56 | 2800 | 0.5473 | 0.5479 | |
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| 1.4696 | 39.5 | 3200 | 0.5002 | 0.5130 | |
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| 1.4175 | 44.44 | 3600 | 0.4752 | 0.5021 | |
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| 1.3943 | 49.38 | 4000 | 0.4638 | 0.4944 | |
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| Pause and Resume | | | | | |
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| 1.3829 | 4.93 | 400 | 0.4290 | 0.4796 | |
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| 1.3156 | 9.87 | 800 | 0.3856 | 0.4474 | |
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| 1.2396 | 14.81 | 1200 | 0.3600 | 0.4307 | |
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| 1.1444 | 19.75 | 1600 | 0.3423 | 0.4179 | |
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| 1.0979 | 24.69 | 2000 | 0.3370 | 0.3884 | |
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| 1.0714 | 29.62 | 2400 | 0.3237 | 0.3710 | |
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| 1.0442 | 34.56 | 2800 | 0.3336 | 0.3683 | |
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| 1.0492 | 39.5 | 3200 | 0.3166 | 0.3527 | |
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| 1.0284 | 44.44 | 3600 | 0.3178 | 0.3566 | |
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| 1.0302 | 49.38 | 4000 | 0.3142 | 0.3512 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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