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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large-v2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: finetune_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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# finetune_base |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2932 |
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- Cer: 8.8686 |
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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: 5e-06 |
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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: 500 |
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- training_steps: 4000 |
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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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| 0.0863 | 2.76 | 1000 | 0.2303 | 9.1216 | |
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| 0.0154 | 5.52 | 2000 | 0.2505 | 8.6437 | |
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| 0.002 | 8.29 | 3000 | 0.2877 | 8.6297 | |
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| 0.0021 | 11.05 | 4000 | 0.2932 | 8.8686 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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