metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny
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: 0.3382526564344746
whisper-tiny
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: 0.5278
- Wer Ortho: 0.3436
- Wer: 0.3383
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 120
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 3.4388 | 1.43 | 20 | 2.2576 | 0.5022 | 0.4038 |
| 1.1317 | 2.86 | 40 | 0.5981 | 0.4047 | 0.3932 |
| 0.3235 | 4.29 | 60 | 0.4967 | 0.3720 | 0.3707 |
| 0.138 | 5.71 | 80 | 0.5035 | 0.3356 | 0.3282 |
| 0.0563 | 7.14 | 100 | 0.5198 | 0.3362 | 0.3294 |
| 0.033 | 8.57 | 120 | 0.5278 | 0.3436 | 0.3383 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0