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--- |
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license: apache-2.0 |
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tags: |
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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: wav2vec2-large-asr-th |
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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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# wav2vec2-large-asr-th |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5920 |
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- Wer: 0.5256 |
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- Cer: 0.1778 |
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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: 2 |
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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: 200 |
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- training_steps: 6000 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 3.6977 | 0.57 | 500 | 3.6087 | 1.0 | 0.9999 | |
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| 3.4771 | 1.14 | 1000 | 3.4975 | 1.0 | 0.9999 | |
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| 2.6942 | 1.71 | 1500 | 2.2851 | 1.0067 | 0.6597 | |
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| 1.698 | 2.28 | 2000 | 1.0650 | 0.7875 | 0.3045 | |
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| 1.5008 | 2.85 | 2500 | 0.8698 | 0.6838 | 0.2508 | |
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| 1.1706 | 3.42 | 3000 | 0.7382 | 0.6132 | 0.2140 | |
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| 1.1872 | 4.0 | 3500 | 0.6924 | 0.5840 | 0.2029 | |
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| 1.1422 | 4.57 | 4000 | 0.6531 | 0.5690 | 0.1959 | |
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| 0.9556 | 5.14 | 4500 | 0.6246 | 0.5432 | 0.1850 | |
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| 1.0091 | 5.71 | 5000 | 0.6052 | 0.5360 | 0.1822 | |
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| 1.0523 | 6.28 | 5500 | 0.5995 | 0.5293 | 0.1802 | |
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| 1.0205 | 6.85 | 6000 | 0.5920 | 0.5256 | 0.1778 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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