metadata
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: whisper_medium_finetuning_maior4s_8kh
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: pt
split: None
args: pt
metrics:
- name: Wer
type: wer
value: 26.357459011283584
whisper_medium_finetuning_maior4s_8kh
This model is a fine-tuned version of openai/whisper-medium on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2421
- Wer: 26.3575
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-06
- train_batch_size: 16
- 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: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1168 | 1.0707 | 1000 | 0.1729 | 24.3127 |
| 0.087 | 2.1413 | 2000 | 0.1663 | 18.2013 |
| 0.058 | 3.2120 | 3000 | 0.1709 | 19.9302 |
| 0.0499 | 4.2827 | 4000 | 0.1780 | 21.3661 |
| 0.0336 | 5.3533 | 5000 | 0.1948 | 25.4951 |
| 0.029 | 6.4240 | 6000 | 0.2105 | 27.6541 |
| 0.0245 | 7.4946 | 7000 | 0.2315 | 26.5528 |
| 0.0195 | 8.5653 | 8000 | 0.2421 | 26.3575 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.19.2
- Tokenizers 0.19.1