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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: ./openai/whisper-large-v3-cit-do015-wd0-lr5e-06-1000 |
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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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# ./openai/whisper-large-v3-cit-do015-wd0-lr5e-06-1000 |
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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 1000 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4753 |
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- Wer Ortho: 23.5867 |
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- Wer: 12.4052 |
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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: 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 Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
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| No log | 0.4444 | 25 | 1.1494 | 33.5283 | 21.6616 | |
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| 1.2689 | 0.8889 | 50 | 0.6362 | 28.0702 | 14.9090 | |
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| 1.2689 | 1.3333 | 75 | 0.5078 | 24.3275 | 12.2534 | |
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| 0.5452 | 1.7778 | 100 | 0.3860 | 23.1189 | 11.7602 | |
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| 0.5452 | 2.2222 | 125 | 0.3789 | 23.1969 | 11.1912 | |
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| 0.3251 | 2.6667 | 150 | 0.3691 | 24.0546 | 11.4568 | |
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| 0.3251 | 3.1111 | 175 | 0.3545 | 23.9376 | 11.5706 | |
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| 0.2441 | 3.5556 | 200 | 0.3701 | 25.3411 | 13.2018 | |
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| 0.2441 | 4.0 | 225 | 0.3564 | 21.4815 | 9.9393 | |
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| 0.1651 | 4.4444 | 250 | 0.3909 | 22.5731 | 10.3566 | |
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| 0.1651 | 4.8889 | 275 | 0.3708 | 24.6394 | 13.0121 | |
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| 0.1394 | 5.3333 | 300 | 0.3928 | 24.7563 | 13.2018 | |
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| 0.1394 | 5.7778 | 325 | 0.4097 | 24.6784 | 13.2018 | |
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| 0.1062 | 6.2222 | 350 | 0.4270 | 25.3021 | 13.4294 | |
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| 0.1062 | 6.6667 | 375 | 0.4133 | 24.2105 | 12.8225 | |
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| 0.0831 | 7.1111 | 400 | 0.4275 | 23.9766 | 13.0880 | |
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| 0.0831 | 7.5556 | 425 | 0.4592 | 23.1579 | 12.3293 | |
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| 0.065 | 8.0 | 450 | 0.4617 | 23.9376 | 12.5190 | |
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| 0.065 | 8.4444 | 475 | 0.4685 | 23.5088 | 12.4810 | |
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| 0.0558 | 8.8889 | 500 | 0.4753 | 23.5867 | 12.4052 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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