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README.md
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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-base
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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-base
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2522
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- Wer: 23.1797
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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: 64
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- eval_batch_size: 64
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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: 10000
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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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| 2.1114 | 0.0 | 1 | 2.3698 | 75.1864 |
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| 0.3272 | 0.29 | 1000 | 0.4182 | 37.7505 |
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| 0.251 | 0.58 | 2000 | 0.3408 | 30.9679 |
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| 0.2207 | 0.88 | 3000 | 0.3059 | 28.3058 |
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| 0.1779 | 1.17 | 4000 | 0.2890 | 26.7555 |
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| 0.1691 | 1.46 | 5000 | 0.2742 | 25.2099 |
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| 0.1622 | 1.75 | 6000 | 0.2645 | 24.6840 |
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| 0.1397 | 2.04 | 7000 | 0.2587 | 23.8812 |
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| 0.1394 | 2.34 | 8000 | 0.2562 | 23.6586 |
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| 0.1361 | 2.63 | 9000 | 0.2536 | 23.4633 |
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| 0.1356 | 2.92 | 10000 | 0.2522 | 23.1797 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 2.0.0
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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