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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: 0.5172 |
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- Cer: 0.1076 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 8 |
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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: 40 |
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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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| 6.742 | 2.6 | 1500 | 0.9038 | 0.2330 | |
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| 0.9228 | 5.2 | 3000 | 0.6193 | 0.1656 | |
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| 0.6805 | 7.8 | 4500 | 0.5522 | 0.1481 | |
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| 0.5577 | 10.4 | 6000 | 0.5136 | 0.1349 | |
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| 0.4797 | 13.0 | 7500 | 0.5074 | 0.1312 | |
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| 0.4161 | 15.6 | 9000 | 0.4959 | 0.1243 | |
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| 0.3701 | 18.21 | 10500 | 0.4948 | 0.1224 | |
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| 0.3307 | 20.81 | 12000 | 0.4881 | 0.1199 | |
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| 0.2946 | 23.41 | 13500 | 0.4970 | 0.1179 | |
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| 0.2636 | 26.01 | 15000 | 0.4950 | 0.1145 | |
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| 0.2367 | 28.61 | 16500 | 0.4905 | 0.1119 | |
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| 0.2157 | 31.21 | 18000 | 0.5066 | 0.1110 | |
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| 0.1979 | 33.81 | 19500 | 0.5133 | 0.1103 | |
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| 0.1808 | 36.41 | 21000 | 0.5160 | 0.1091 | |
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| 0.17 | 39.01 | 22500 | 0.5129 | 0.1074 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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