metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: minds14-finetuned
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train[450:]
args: en-US
metrics:
- name: Wer
type: wer
value: 0.35780382479950645
minds14-finetuned
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: 0.6602
- Wer Ortho: 0.3412
- Wer: 0.3578
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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 4.8952 | 1.0 | 28 | 2.9786 | 0.4097 | 0.5373 |
| 2.0364 | 2.0 | 56 | 0.7791 | 0.3813 | 0.4275 |
| 0.5903 | 3.0 | 84 | 0.5917 | 0.3506 | 0.3917 |
| 0.3271 | 4.0 | 112 | 0.5681 | 0.3129 | 0.3381 |
| 0.2543 | 5.0 | 140 | 0.5713 | 0.3365 | 0.3652 |
| 0.1391 | 6.0 | 168 | 0.5896 | 0.3329 | 0.3621 |
| 0.0846 | 7.0 | 196 | 0.6083 | 0.3388 | 0.3658 |
| 0.0481 | 8.0 | 224 | 0.6209 | 0.3583 | 0.3738 |
| 0.0148 | 9.0 | 252 | 0.6625 | 0.3477 | 0.3689 |
| 0.0087 | 10.0 | 280 | 0.6602 | 0.3412 | 0.3578 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3