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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

TypeText modelModèle de baseopenai/whisper-large-v3-turboVersionmodelBClasse

Source du modèle

Type
Text model
Taille du fichier
3,01 GB
Modèle de base
openai/whisper-large-v3-turbo
Version
vmodel
Mis à jour
26 oct. 2026
Téléchargements
4
Source
Hugging Face

Description de la source

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 LossEpochStepValidation LossGlobal Wer
0.22351.261010000.269352.5266
0.14952.522120000.257048.6965
0.11563.783130000.268147.2353
0.09065.044140000.292147.0615
0.05586.305250000.308146.6495

Framework versions

  • Transformers 4.50.0
  • Pytorch 2.9.0+cu126
  • Datasets 3.6.0
  • Tokenizers 0.21.4

Sources

1 source

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 3,01 GB · SHA-256 37453bef7523…0392 · Hugging Face

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Extraits de sources

3 extraits

--- 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