metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-small-mix-pt
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: pt
split: test
args: pt
metrics:
- name: Wer
type: wer
value: 10.670098148917804
whisper-small-mix-pt
This model is a fine-tuned version of openai/whisper-small on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2007
- Wer: 10.6701
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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1575 | 0.2 | 1000 | 0.2125 | 12.1855 |
| 0.1986 | 0.4 | 2000 | 0.2062 | 11.5701 |
| 0.0942 | 1.131 | 3000 | 0.1979 | 11.0154 |
| 0.0577 | 1.331 | 4000 | 0.2000 | 10.6349 |
| 0.0516 | 2.062 | 5000 | 0.2007 | 10.6701 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1