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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: whisper-base-en |
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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-base-en |
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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: 0.1362 |
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- Wer: 4.3516 |
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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: 16 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 3000 |
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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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| 0.0146 | 0.4 | 100 | 0.1223 | 4.8708 | |
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| 0.0159 | 0.8 | 200 | 0.1248 | 4.8306 | |
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| 0.0104 | 1.2 | 300 | 0.1251 | 4.3803 | |
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| 0.01 | 1.6 | 400 | 0.1259 | 4.3975 | |
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| 0.0092 | 2.0 | 500 | 0.1263 | 4.4749 | |
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| 0.0055 | 2.4 | 600 | 0.1301 | 4.3344 | |
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| 0.0062 | 2.8 | 700 | 0.1303 | 4.4061 | |
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| 0.0039 | 3.2 | 800 | 0.1324 | 4.5294 | |
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| 0.0045 | 3.6 | 900 | 0.1337 | 4.3889 | |
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| 0.0036 | 4.0 | 1000 | 0.1350 | 4.2626 | |
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| 0.0033 | 4.4 | 1100 | 0.1358 | 4.3344 | |
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| 0.0033 | 4.8 | 1200 | 0.1362 | 4.3516 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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