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--- |
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language: |
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- te |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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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 Small Te - Bharat Ramanathan |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: google/fleurs |
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type: google/fleurs |
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config: te_in |
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split: test |
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metrics: |
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- type: wer |
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value: 30.26 |
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name: WER |
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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 Small Te - Bharat Ramanathan |
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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: 0.1863 |
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- Wer: 31.6456 |
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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: 32 |
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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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| 0.1637 | 0.1 | 500 | 0.2092 | 42.9406 | |
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| 0.1459 | 0.2 | 1000 | 0.2025 | 35.9299 | |
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| 0.1348 | 0.3 | 1500 | 0.1990 | 35.4917 | |
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| 0.1309 | 0.4 | 2000 | 0.1974 | 33.7390 | |
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| 0.1253 | 0.5 | 2500 | 0.1974 | 34.0312 | |
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| 0.1209 | 0.6 | 3000 | 0.1909 | 32.4732 | |
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| 0.1139 | 1.05 | 3500 | 0.1899 | 31.7916 | |
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| 0.1043 | 1.15 | 4000 | 0.1868 | 31.6456 | |
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| 0.0996 | 1.25 | 4500 | 0.1874 | 31.6943 | |
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| 0.1002 | 1.35 | 5000 | 0.1863 | 31.6456 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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