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--- |
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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-baset |
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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-baset |
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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: 0.0001 |
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- Wer: 1.9802 |
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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: 1 |
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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: linear |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 1000 |
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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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| No log | 100.0 | 100 | 0.0009 | 1.9802 | |
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| No log | 200.0 | 200 | 0.0003 | 1.9802 | |
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| No log | 300.0 | 300 | 0.0002 | 1.9802 | |
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| No log | 400.0 | 400 | 0.0001 | 1.9802 | |
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| 0.0555 | 500.0 | 500 | 0.0001 | 1.9802 | |
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| 0.0555 | 600.0 | 600 | 0.0001 | 1.9802 | |
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| 0.0555 | 700.0 | 700 | 0.0001 | 1.9802 | |
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| 0.0555 | 800.0 | 800 | 0.0001 | 1.9802 | |
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| 0.0555 | 900.0 | 900 | 0.0001 | 1.9802 | |
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| 0.0001 | 1000.0 | 1000 | 0.0001 | 1.9802 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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