metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
metrics:
- name: Wer
type: wer
value: 0.3482880755608028
whisper-tiny-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: 0.4687
- Wer: 0.3483
- Wer Ortho: 0.3609
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: 8
- seed: 42
- 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: 100
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho |
|---|---|---|---|---|---|
| 3.2197 | 1.0 | 29 | 2.3350 | 0.3973 | 0.5231 |
| 1.8109 | 2.0 | 58 | 0.6575 | 0.3796 | 0.4170 |
| 0.6252 | 3.0 | 87 | 0.4859 | 0.3583 | 0.3720 |
| 0.3612 | 4.0 | 116 | 0.4680 | 0.3613 | 0.3726 |
| 0.2543 | 5.0 | 145 | 0.4687 | 0.3483 | 0.3609 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.1.1
- Tokenizers 0.22.1