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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-tiny-fluers_V2_telugu_Augmentation_full_datset_V2_e5 |
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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-tiny-fluers_V2_telugu_Augmentation_full_datset_V2_e5 |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3374 |
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- Wer: 61.2000 |
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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: 1.5e-05 |
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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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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06 |
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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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| 1.2926 | 0.09 | 300 | 1.3993 | 129.5 | |
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| 1.0948 | 0.18 | 600 | 1.2674 | 109.1500 | |
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| 0.6591 | 0.28 | 900 | 0.5519 | 81.55 | |
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| 0.5326 | 0.37 | 1200 | 0.4361 | 72.55 | |
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| 0.4737 | 0.46 | 1500 | 0.4036 | 69.2000 | |
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| 0.4239 | 0.55 | 1800 | 0.3793 | 63.6 | |
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| 0.4011 | 0.64 | 2100 | 0.3625 | 62.2500 | |
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| 0.3687 | 0.73 | 2400 | 0.3651 | 62.5 | |
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| 0.3712 | 0.83 | 2700 | 0.3491 | 59.9 | |
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| 0.3686 | 0.92 | 3000 | 0.3438 | 60.6500 | |
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| 0.3381 | 1.01 | 3300 | 0.3391 | 58.25 | |
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| 0.3483 | 1.1 | 3600 | 0.3385 | 60.0500 | |
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| 0.341 | 1.19 | 3900 | 0.3374 | 61.2000 | |
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### Framework versions |
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- Transformers 4.28.0.dev0 |
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- Pytorch 1.12.1 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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