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--- |
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library_name: transformers |
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language: |
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- en |
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license: cc-by-sa-4.0 |
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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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- sage-bergerson/edacc_processed |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large EdAcc V2 |
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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: EdAcc |
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type: sage-bergerson/edacc_processed |
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args: 'config: en, split: train' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.5855270257403117 |
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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 EdAcc V2 |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the EdAcc dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6378 |
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- Wer: 0.5855 |
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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: 5e-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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: 1000 |
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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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| 1.1515 | 0.3247 | 100 | 0.7869 | 0.3055 | |
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| 0.6272 | 0.6494 | 200 | 0.6171 | 0.4607 | |
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| 0.5614 | 0.9740 | 300 | 0.5925 | 0.6110 | |
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| 0.43 | 1.2987 | 400 | 0.5868 | 0.5105 | |
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| 0.4576 | 1.6234 | 500 | 0.5844 | 0.6095 | |
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| 0.4727 | 1.9481 | 600 | 0.5784 | 0.6796 | |
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| 0.3274 | 2.2727 | 700 | 0.6094 | 0.5416 | |
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| 0.2862 | 2.5974 | 800 | 0.6027 | 0.5609 | |
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| 0.2908 | 2.9221 | 900 | 0.6107 | 0.4607 | |
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| 0.2221 | 3.2468 | 1000 | 0.6378 | 0.5855 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
