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language: |
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- en |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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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-large-cit-do0.2-wd0.001-tr5 |
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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-large-cit-do0.2-wd0.001-tr5 |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the SF 200 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8701 |
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- Wer: 28.8330 |
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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: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 100 |
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- training_steps: 200 |
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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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| 1.0205 | 0.8889 | 10 | 0.8452 | 34.3249 | |
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| 0.7299 | 1.7778 | 20 | 0.6455 | 31.1213 | |
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| 0.48 | 2.6667 | 30 | 0.5552 | 30.4348 | |
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| 0.291 | 3.5556 | 40 | 0.5288 | 30.6636 | |
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| 0.1931 | 4.4444 | 50 | 0.5479 | 28.3753 | |
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| 0.107 | 5.3333 | 60 | 0.6104 | 29.0618 | |
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| 0.0622 | 6.2222 | 70 | 0.6509 | 28.8330 | |
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| 0.0271 | 7.1111 | 80 | 0.7900 | 30.4348 | |
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| 0.0198 | 8.0 | 90 | 0.7246 | 30.2059 | |
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| 0.0176 | 8.8889 | 100 | 0.6992 | 27.6888 | |
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| 0.0163 | 9.7778 | 110 | 0.7896 | 29.5195 | |
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| 0.0087 | 10.6667 | 120 | 0.7793 | 30.4348 | |
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| 0.0092 | 11.5556 | 130 | 0.8213 | 28.8330 | |
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| 0.0063 | 12.4444 | 140 | 0.8369 | 29.5195 | |
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| 0.0038 | 13.3333 | 150 | 0.8262 | 29.7483 | |
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| 0.0036 | 14.2222 | 160 | 0.8506 | 28.3753 | |
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| 0.0021 | 15.1111 | 170 | 0.8647 | 29.5195 | |
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| 0.0017 | 16.0 | 180 | 0.8608 | 29.5195 | |
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| 0.0012 | 16.8889 | 190 | 0.8662 | 28.8330 | |
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| 0.001 | 17.7778 | 200 | 0.8701 | 28.8330 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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