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-en
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train
args: en-US
metrics:
- name: Wer
type: wer
value: 0.33766233766233766
whisper-tiny-en
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: 0.8729
- Wer Ortho: 0.3344
- Wer: 0.3377
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0006 | 17.8571 | 500 | 0.6617 | 0.3251 | 0.3264 |
| 0.0002 | 35.7143 | 1000 | 0.7217 | 0.3257 | 0.3270 |
| 0.0001 | 53.5714 | 1500 | 0.7577 | 0.3226 | 0.3247 |
| 0.0001 | 71.4286 | 2000 | 0.7870 | 0.3337 | 0.3347 |
| 0.0 | 89.2857 | 2500 | 0.8109 | 0.3325 | 0.3341 |
| 0.0 | 107.1429 | 3000 | 0.8329 | 0.3356 | 0.3377 |
| 0.0 | 125.0 | 3500 | 0.8529 | 0.3344 | 0.3371 |
| 0.0 | 142.8571 | 4000 | 0.8729 | 0.3344 | 0.3377 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1