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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-large-v2-atcosim |
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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-v2-atcosim |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0552 |
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- Wer: 9.9694 |
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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: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- total_train_batch_size: 64 |
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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: 250 |
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- training_steps: 12500 |
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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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| 0.0038 | 8.33 | 1000 | 0.0357 | 2.7829 | |
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| 0.001 | 16.67 | 2000 | 0.0384 | 2.0004 | |
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| 0.0015 | 25.0 | 3000 | 0.0373 | 31.7142 | |
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| 0.0001 | 33.33 | 4000 | 0.0437 | 2.3152 | |
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| 0.0019 | 41.67 | 5000 | 0.0446 | 7.2375 | |
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| 0.0 | 50.0 | 6000 | 0.0462 | 2.9033 | |
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| 0.0 | 58.33 | 7000 | 0.0490 | 4.3295 | |
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| 0.0 | 66.67 | 8000 | 0.0509 | 5.8668 | |
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| 0.0 | 75.0 | 9000 | 0.0524 | 7.5014 | |
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| 0.0 | 83.33 | 10000 | 0.0536 | 8.6405 | |
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| 0.0 | 91.67 | 11000 | 0.0546 | 9.5018 | |
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| 0.0 | 100.0 | 12000 | 0.0552 | 9.9694 | |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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