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--- |
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language: |
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- zh |
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base_model: Kathernie/whisper-small-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- custom_datset |
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model-index: |
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- name: Whisper Small Chinese MOE Response |
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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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# Whisper Small Chinese MOE Response |
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This model is a fine-tuned version of [Kathernie/whisper-small-all](https://huggingface.co/Kathernie/whisper-small-all) on the MOE Response Chinese dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2640 |
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- Cer: 11.0180 |
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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: 8 |
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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: 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: 250 |
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- training_steps: 2000 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:-------:| |
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| 0.2252 | 1.0811 | 200 | 0.2339 | 12.4230 | |
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| 0.1268 | 2.1622 | 400 | 0.2223 | 10.9194 | |
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| 0.056 | 3.2432 | 600 | 0.2242 | 10.8701 | |
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| 0.023 | 4.3243 | 800 | 0.2387 | 11.3384 | |
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| 0.01 | 5.4054 | 1000 | 0.2546 | 11.2645 | |
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| 0.0044 | 6.4865 | 1200 | 0.2515 | 11.2891 | |
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| 0.0028 | 7.5676 | 1400 | 0.2552 | 10.9440 | |
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| 0.0017 | 8.6486 | 1600 | 0.2623 | 11.2645 | |
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| 0.0017 | 9.7297 | 1800 | 0.2624 | 10.9933 | |
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| 0.001 | 10.8108 | 2000 | 0.2640 | 11.0180 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.2.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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