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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- automatic-speech-recognition |
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- ./sample_speech.py |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: ko-xlsr |
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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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# ko-xlsr |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4228 |
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- Cer: 0.1091 |
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- Wer: 0.3025 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 16 |
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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: 1000 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 1.5566 | 0.94 | 2000 | 1.0226 | 0.2632 | 0.6184 | |
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| 1.179 | 1.89 | 4000 | 0.7682 | 0.2001 | 0.4990 | |
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| 1.0432 | 2.83 | 6000 | 0.6633 | 0.1749 | 0.4516 | |
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| 0.9413 | 3.77 | 8000 | 0.6159 | 0.1624 | 0.4259 | |
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| 0.8765 | 4.72 | 10000 | 0.5792 | 0.1538 | 0.4061 | |
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| 0.8248 | 5.66 | 12000 | 0.5456 | 0.1446 | 0.3877 | |
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| 0.7714 | 6.6 | 14000 | 0.5316 | 0.1397 | 0.3710 | |
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| 0.7388 | 7.55 | 16000 | 0.5172 | 0.1356 | 0.3657 | |
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| 0.6912 | 8.49 | 18000 | 0.4892 | 0.1291 | 0.3508 | |
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| 0.6549 | 9.43 | 20000 | 0.4694 | 0.1241 | 0.3397 | |
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| 0.614 | 10.37 | 22000 | 0.4615 | 0.1205 | 0.3309 | |
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| 0.5901 | 11.32 | 24000 | 0.4489 | 0.1177 | 0.3215 | |
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| 0.555 | 12.26 | 26000 | 0.4419 | 0.1148 | 0.3163 | |
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| 0.5377 | 13.2 | 28000 | 0.4320 | 0.1122 | 0.3103 | |
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| 0.5253 | 14.15 | 30000 | 0.4251 | 0.1102 | 0.3052 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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