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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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- swagen |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-medium-swagen-combined-15hrs-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: swagen |
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type: swagen |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.27171266233766234 |
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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-swagen-combined-15hrs-model |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the swagen dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4103 |
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- Wer: 0.2717 |
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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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- num_epochs: 30.0 |
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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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| 2.6268 | 0.1654 | 200 | 0.8031 | 0.4605 | |
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| 2.0712 | 0.3308 | 400 | 0.6148 | 0.3829 | |
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| 1.7302 | 0.4962 | 600 | 0.5562 | 0.3490 | |
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| 1.5735 | 0.6616 | 800 | 0.5103 | 0.3106 | |
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| 1.5623 | 0.8270 | 1000 | 0.4683 | 0.2776 | |
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| 1.2713 | 0.9924 | 1200 | 0.4439 | 0.2688 | |
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| 0.7209 | 1.1571 | 1400 | 0.4601 | 0.2732 | |
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| 0.6856 | 1.3225 | 1600 | 0.4391 | 0.2595 | |
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| 0.7661 | 1.4879 | 1800 | 0.4396 | 0.2755 | |
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| 0.8113 | 1.6533 | 2000 | 0.4262 | 0.2643 | |
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| 0.77 | 1.8187 | 2200 | 0.4175 | 0.2679 | |
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| 0.6942 | 1.9841 | 2400 | 0.4103 | 0.2717 | |
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| 0.2814 | 2.1489 | 2600 | 0.4295 | 0.2617 | |
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| 0.3171 | 2.3142 | 2800 | 0.4301 | 0.2432 | |
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| 0.3495 | 2.4796 | 3000 | 0.4299 | 0.2526 | |
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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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