Downloads · 30 days
4
6% of all-time downloads
whisper-medium-cv17-es-500-steps_proc3-def3
mmarron14/whisper-medium-cv17-es-500-steps_proc3-def3
whisper-medium-cv17-es-500-steps_proc3-def3 is a automatic speech recognition model from mmarron14. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
67
Public
Parameters
764M
15.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors3.1 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Dec 8, 2025
- Updated
- Dec 9, 2025
- SHA
- 1cce7270
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
Whisper Medium CV17 Es 500 steps with same training configuration as 500-steps_proc2-def3 -with filtering 30sec, customised optimizer, and same training_args -; but with processing of text using method 3 - María Marrón
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1708
- Wer Ortho: 10.2104
- Wer: 5.9175
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: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.2126 | 0.2 | 100 | 0.1915 | 11.4950 | 7.0113 |
| 0.1861 | 0.4 | 200 | 0.1843 | 11.2696 | 6.5645 |
| 0.1902 | 0.6 | 300 | 0.1785 | 10.6012 | 6.2633 |
| 0.1741 | 0.8 | 400 | 0.1735 | 10.3084 | 5.9830 |
| 0.1796 | 1.0 | 500 | 0.1708 | 10.2104 | 5.9175 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.9.1+cu128
- Datasets 2.14.4
- Tokenizers 0.21.4
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- es
- Created
- Dec 8, 2025
- Updated
- Dec 9, 2025