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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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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: xwhisper-kh-base |
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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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# xwhisper-kh-base |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2711 |
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- Wer: 74.0769 |
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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: 1e-05 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 10 |
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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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| 0.8338 | 1.0 | 1087 | 0.4122 | 90.5307 | |
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| 0.3136 | 2.0 | 2174 | 0.3022 | 80.1699 | |
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| 0.2199 | 3.0 | 3261 | 0.2599 | 76.6601 | |
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| 0.1675 | 4.0 | 4348 | 0.2483 | 74.3577 | |
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| 0.1294 | 5.0 | 5435 | 0.2483 | 72.6309 | |
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| 0.1001 | 6.0 | 6522 | 0.2555 | 74.8982 | |
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| 0.0759 | 7.0 | 7609 | 0.2711 | 74.0769 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.4.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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