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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-Timit-fineT-16
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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-Timit-fineT-16
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1388
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- Wer: 38.9999
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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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- 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: 5000
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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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| 0.0356 | 1.73 | 500 | 0.0982 | 61.5030 |
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| 0.0022 | 3.46 | 1000 | 0.1059 | 80.2039 |
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| 0.0018 | 5.19 | 1500 | 0.1167 | 47.5479 |
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| 0.0002 | 6.92 | 2000 | 0.1204 | 49.5247 |
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| 0.0002 | 8.65 | 2500 | 0.1280 | 51.4465 |
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| 0.0001 | 10.38 | 3000 | 0.1316 | 44.9029 |
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| 0.0001 | 12.11 | 3500 | 0.1345 | 42.7538 |
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| 0.0001 | 13.84 | 4000 | 0.1368 | 40.0744 |
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| 0.0001 | 15.57 | 4500 | 0.1382 | 40.0813 |
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| 0.0001 | 17.3 | 5000 | 0.1388 | 38.9999 |
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 1.13.0
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- Datasets 2.1.0
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- Tokenizers 0.13.2
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