Whisper Tiny En Minds14
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set: Loss: 0.5909 Wer Ortho: 0.3288 Wer: 0.3241
Model source
- Kind
- Text model
- File size
- 144 MB
- Base model
- openai/whisper-tiny
- Version
- vFP32
- Updated
- Oct 31, 2026
- Downloads
- 6
- Source
- Hugging Face
Source description
whisper-tiny-en-minds14
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5909
- Wer Ortho: 0.3288
- Wer: 0.3241
Model description
openai/whisper-tiny
Intended uses & limitations
automatic-speech-recognition
Training and evaluation data
PolyAI/minds14
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 5.6090 | 0.8929 | 25 | 1.9933 | 0.4775 | 0.3867 |
| 1.0683 | 1.7857 | 50 | 0.5234 | 0.3812 | 0.3701 |
| 0.6299 | 2.6786 | 75 | 0.4771 | 0.3553 | 0.3424 |
| 0.4853 | 3.5714 | 100 | 0.4679 | 0.3405 | 0.3335 |
| 0.3242 | 4.4643 | 125 | 0.4824 | 0.3584 | 0.3489 |
| 0.1566 | 5.3571 | 150 | 0.4964 | 0.3325 | 0.3235 |
| 0.1353 | 6.25 | 175 | 0.5071 | 0.3374 | 0.3264 |
| 0.0663 | 7.1429 | 200 | 0.5246 | 0.3436 | 0.3335 |
| 0.0493 | 8.0357 | 225 | 0.5306 | 0.3387 | 0.3300 |
| 0.0299 | 8.9286 | 250 | 0.5481 | 0.3362 | 0.3306 |
| 0.0163 | 9.8214 | 275 | 0.5651 | 0.3294 | 0.3253 |
| 0.0076 | 10.7143 | 300 | 0.5702 | 0.3307 | 0.3259 |
| 0.0093 | 11.6071 | 325 | 0.5824 | 0.3307 | 0.3253 |
| 0.0058 | 12.5 | 350 | 0.5861 | 0.3263 | 0.3217 |
| 0.0054 | 13.3929 | 375 | 0.5874 | 0.3307 | 0.3253 |
| 0.0045 | 14.2857 | 400 | 0.5902 | 0.3294 | 0.3247 |
| 0.0048 | 15.0 | 420 | 0.5909 | 0.3288 | 0.3241 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVerified Oct 31
Download files
Repository files
File inventory only; completeness is unverified.
Model artifacts
1 artifact
Model artifacts
1 artifactmodel.safetensors
safetensors · FP32 (unverified) · 144 MB · SHA-256 a4c4dfda7e80…5765 · Hugging Face
Download fileSource excerpts
3 excerpts
Source excerpts
3 excerpts--- library_name: transformers license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer - automatic-speech-recognition datasets: - PolyAI/minds14 metrics: - wer model-index: - name: whisper-tiny-en-minds14 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: PolyAI/minds14 type: PolyAI/minds14 metrics: - name: Wer type: wer value: 0.32408500590318773 --- <!-- 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-tiny-en-minds14 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set: - Loss: 0.5909 - Wer Ortho: 0.3288 - Wer: 0.3241 ## Model description openai/whisper-tiny ## Intended uses & limitations automatic-speech-recognition ## Training and evaluation data PolyAI/minds14 ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1 - num_epochs: 15 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:| | 5.6090 | 0.8929 | 25 | 1.9933 | 0.4775 | 0.3867 | | 1.0683 | 1.7857 | 50 | 0.5234 | 0.3812 | 0.3701 | | 0.6299 | 2.6786 | 75 | 0.4771 | 0.3553 | 0.3424 | | 0.4853 | 3.5714 | 100 | 0.4679 | 0.3405 | 0.3335 | | 0.3242 | 4.4643 | 125 | 0.4824 | 0.3584 | 0.3489 | | 0.1566 | 5.3571 | 150 | 0.4964 | 0.3325 | 0.3235 | | 0.1353 | 6.25 | 175 | 0.5071 | 0.3374 | 0.3264 | | 0.0663 | 7.1429 | 200 | 0.5246 | 0.3436 | 0.3335 | | 0.0493 | 8.0357 | 225 | 0.5306 | 0.3387 | 0.3300 | | 0.0299 | 8.9286 | 250 | 0.5481 | 0.3362 | 0.3306 | | 0.0163 | 9.8214 | 275 | 0.5651 | 0.3294 | 0.3253 | | 0.0076 | 10.7143 | 300 | 0.5702 | 0.3307 | 0.3259 | | 0.0093 | 11.6071 | 325 | 0.5824...
Source context: 6 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo nagorebravo/whisper-tiny-en-minds14
Source context: 86 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo nagorebravo/whisper-tiny-en-minds14
