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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-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- nyagen |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-medium-nyagen-baseline-model |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: nyagen |
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type: nyagen |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.31363034847816496 |
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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-medium-nyagen-baseline-model |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the nyagen dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4721 |
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- Wer: 0.3136 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 500 |
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- training_steps: 5000 |
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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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| 1.6573 | 1.0257 | 200 | 0.7472 | 0.4663 | |
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| 0.8271 | 2.0514 | 400 | 0.4985 | 0.4389 | |
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| 0.4472 | 3.0771 | 600 | 0.4721 | 0.3136 | |
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| 0.1499 | 4.1028 | 800 | 0.4968 | 0.3092 | |
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| 0.064 | 5.1285 | 1000 | 0.4892 | 0.3335 | |
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| 0.0521 | 6.1542 | 1200 | 0.5093 | 0.3048 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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