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--- |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- generator |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-medium-ach-only |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: generator |
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type: generator |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 21.152030217186024 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/bakera-sunbird/huggingface/runs/rycj9ija) |
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# whisper-medium-ach-only |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3942 |
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- Wer: 21.1520 |
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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: 4000 |
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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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| 1.1662 | 0.05 | 200 | 0.7062 | 47.0255 | |
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| 0.6014 | 1.0248 | 400 | 0.4606 | 32.9556 | |
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| 0.5638 | 1.0748 | 600 | 0.4021 | 27.2899 | |
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| 0.3677 | 2.0495 | 800 | 0.3736 | 24.3626 | |
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| 0.2711 | 3.0242 | 1000 | 0.3648 | 23.5127 | |
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| 0.2862 | 3.0743 | 1200 | 0.3402 | 23.7016 | |
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| 0.2023 | 4.049 | 1400 | 0.3665 | 22.4740 | |
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| 0.1166 | 5.0237 | 1600 | 0.4023 | 23.6072 | |
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| 0.1089 | 5.0738 | 1800 | 0.3871 | 22.5685 | |
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| 0.0859 | 6.0485 | 2000 | 0.3837 | 25.6846 | |
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| 0.0557 | 7.0232 | 2200 | 0.3942 | 21.1520 | |
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| 0.0572 | 7.0732 | 2400 | 0.3805 | 22.0963 | |
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| 0.0469 | 8.048 | 2600 | 0.3995 | 23.6072 | |
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| 0.0308 | 9.0228 | 2800 | 0.4057 | 21.5297 | |
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| 0.0288 | 9.0727 | 3000 | 0.3999 | 21.1520 | |
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| 0.0222 | 10.0475 | 3200 | 0.4121 | 21.7186 | |
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| 0.0239 | 11.0222 | 3400 | 0.4162 | 21.9075 | |
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| 0.024 | 11.0723 | 3600 | 0.4154 | 21.9075 | |
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| 0.0219 | 12.047 | 3800 | 0.4186 | 21.3409 | |
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| 0.0133 | 13.0218 | 4000 | 0.4173 | 21.1520 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.19.1 |
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