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--- |
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license: apache-2.0 |
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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-medium-hi |
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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-medium-hi |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3957 |
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- Wer: 0.2425 |
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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: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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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: 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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| 0.0234 | 4.88 | 1000 | 0.2762 | 0.2750 | |
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| 0.003 | 9.76 | 2000 | 0.3342 | 0.2518 | |
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| 0.0001 | 14.63 | 3000 | 0.3636 | 0.2424 | |
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| 0.0 | 19.51 | 4000 | 0.3877 | 0.2426 | |
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| 0.0 | 24.39 | 5000 | 0.3957 | 0.2425 | |
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### Framework versions |
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- Transformers 4.28.0.dev0 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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