metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-finetuned-fullsample-v1
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: 11.31198430186737
whisper-finetuned-fullsample-v1
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3719
- Wer: 11.3120
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- training_steps: 6000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0094 | 8.1384 | 1000 | 0.2714 | 24.2485 |
| 0.0008 | 16.2767 | 2000 | 0.3292 | 25.8955 |
| 0.0011 | 24.4151 | 3000 | 0.3289 | 12.6679 |
| 0.0003 | 32.5534 | 4000 | 0.3546 | 12.0631 |
| 0.0015 | 40.6918 | 5000 | 0.3405 | 12.0647 |
| 0.0002 | 48.8301 | 6000 | 0.3719 | 11.3120 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu124
- Datasets 3.0.2.dev0
- Tokenizers 0.20.0