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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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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: 0.4215 |
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- Cer: 0.1103 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 1.5961 | 0.94 | 2000 | 1.0685 | 0.2712 | |
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| 1.2068 | 1.89 | 4000 | 0.8059 | 0.2117 | |
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| 1.0519 | 2.83 | 6000 | 0.6764 | 0.1784 | |
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| 0.9522 | 3.77 | 8000 | 0.6238 | 0.1667 | |
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| 0.8855 | 4.72 | 10000 | 0.5901 | 0.1572 | |
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| 0.8353 | 5.66 | 12000 | 0.5560 | 0.1473 | |
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| 0.7765 | 6.6 | 14000 | 0.5313 | 0.1418 | |
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| 0.7333 | 7.55 | 16000 | 0.5100 | 0.1339 | |
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| 0.6887 | 8.49 | 18000 | 0.4902 | 0.1304 | |
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| 0.6547 | 9.43 | 20000 | 0.4785 | 0.1252 | |
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| 0.612 | 10.37 | 22000 | 0.4594 | 0.1200 | |
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| 0.5855 | 11.32 | 24000 | 0.4469 | 0.1176 | |
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| 0.5538 | 12.26 | 26000 | 0.4398 | 0.1156 | |
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| 0.5341 | 13.2 | 28000 | 0.4318 | 0.1124 | |
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| 0.5229 | 14.15 | 30000 | 0.4251 | 0.1111 | |
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### Framework versions |
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- Transformers 4.34.0 |
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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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