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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-large |
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tags: |
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- generated_from_trainer |
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datasets: |
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- deepinfinityai/30_report_sentences_dataset |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper_Large_30_sent_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: 11 Sentences |
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type: deepinfinityai/30_report_sentences_dataset |
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metrics: |
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- name: Wer |
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type: wer |
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value: 169.6969696969697 |
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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_Large_30_sent_Model |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the 11 Sentences dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8472 |
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- Wer: 169.6970 |
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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: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 50 |
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- training_steps: 500 |
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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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| 2.3891 | 8.3333 | 50 | 1.2466 | 21.2121 | |
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| 0.0553 | 16.6667 | 100 | 0.1580 | 18.1818 | |
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| 0.0002 | 25.0 | 150 | 0.1879 | 157.5758 | |
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| 0.0002 | 33.3333 | 200 | 0.2462 | 87.8788 | |
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| 0.0001 | 41.6667 | 250 | 0.3595 | 200.0 | |
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| 0.0001 | 50.0 | 300 | 0.5265 | 190.9091 | |
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| 0.0001 | 58.3333 | 350 | 0.6597 | 184.8485 | |
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| 0.0001 | 66.6667 | 400 | 0.7327 | 175.7576 | |
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| 0.0001 | 75.0 | 450 | 0.8169 | 172.7273 | |
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| 0.0001 | 83.3333 | 500 | 0.8472 | 169.6970 | |
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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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