Wh L v3 T Iv Indic Voices 59403 Text Normalized Ratio 30 70 Lg Hi Val FT
This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.3081 Global Wer: 46.6495
Model source
- Kind
- Text model
- File size
- 3.01 GB
- Base model
- openai/whisper-large-v3-turbo
- Version
- vmodel
- Updated
- Oct 26, 2026
- Downloads
- 4
- Source
- Hugging Face
Source description
wh_l_v3_t_iv_indic_voices_59403_text_normalized_ratio_30_70_lg_hi_val_FT
This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3081
- Global Wer: 46.6495
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Global Wer |
|---|---|---|---|---|
| 0.2235 | 1.2610 | 1000 | 0.2693 | 52.5266 |
| 0.1495 | 2.5221 | 2000 | 0.2570 | 48.6965 |
| 0.1156 | 3.7831 | 3000 | 0.2681 | 47.2353 |
| 0.0906 | 5.0441 | 4000 | 0.2921 | 47.0615 |
| 0.0558 | 6.3052 | 5000 | 0.3081 | 46.6495 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.9.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4
Sources
1 source
Sources
1 sourceVerified Oct 26
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
3 excerpts
Source excerpts
3 excerpts--- library_name: transformers license: mit base_model: openai/whisper-large-v3-turbo tags: - generated_from_trainer model-index: - name: wh_l_v3_t_iv_indic_voices_59403_text_normalized_ratio_30_70_lg_hi_val_FT results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # wh_l_v3_t_iv_indic_voices_59403_text_normalized_ratio_30_70_lg_hi_val_FT This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3081 - Global Wer: 46.6495 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 500 - training_steps: 5000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Global Wer | |:-------------:|:------:|:----:|:---------------:|:----------:| | 0.2235 | 1.2610 | 1000 | 0.2693 | 52.5266 | | 0.1495 | 2.5221 | 2000 | 0.2570 | 48.6965 | | 0.1156 | 3.7831 | 3000 | 0.2681 | 47.2353 | | 0.0906 | 5.0441 | 4000 | 0.2921 | 47.0615 | | 0.0558 | 6.3052 | 5000 | 0.3081 | 46.6495 | ### Framework versions - Transformers 4.50.0 - Pytorch 2.9.0+cu126 - Datasets 3.6.0 - Tokenizers 0.21.4
Source context: 4 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo dianavdavidson/wh_l_v3_t_iv_indic_voices_59403_text_normalized_ratio_30_70_lg_hi_val_FT
Source context: 22 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo dianavdavidson/wh_l_v3_t_iv_indic_voices_59403_text_normalized_ratio_30_70_lg_hi_val_FT
