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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-10hrs-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: 0.3075245365321701 |
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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-10hrs-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: 0.4674 |
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- Wer: 0.3075 |
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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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| 2.6418 | 0.2385 | 200 | 0.8312 | 0.4835 | |
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| 1.9381 | 0.4769 | 400 | 0.6574 | 0.4050 | |
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| 1.7528 | 0.7154 | 600 | 0.5706 | 0.3545 | |
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| 1.7421 | 0.9538 | 800 | 0.5140 | 0.3504 | |
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| 0.9259 | 1.1931 | 1000 | 0.5175 | 0.3262 | |
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| 0.8254 | 1.4316 | 1200 | 0.4978 | 0.3096 | |
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| 0.9616 | 1.6700 | 1400 | 0.4755 | 0.2999 | |
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| 0.7893 | 1.9085 | 1600 | 0.4674 | 0.3075 | |
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| 0.3547 | 2.1478 | 1800 | 0.4848 | 0.3158 | |
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| 0.3568 | 2.3863 | 2000 | 0.4913 | 0.2616 | |
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| 0.3759 | 2.6247 | 2200 | 0.4685 | 0.3104 | |
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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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