metadata
library_name: peft
language:
- it
base_model: b-brave/asr_double_training_15-10-2024_merged
tags:
- generated_from_trainer
datasets:
- ASR_BB_and_EC
metrics:
- wer
model-index:
- name: Whisper Medium
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: ASR_BB_and_EC
type: ASR_BB_and_EC
config: default
split: test
args: default
metrics:
- type: wer
value: 36.926889714993806
name: Wer
Whisper Medium
This model is a fine-tuned version of b-brave/asr_double_training_15-10-2024_merged on the ASR_BB_and_EC dataset. It achieves the following results on the evaluation set:
- Loss: 0.4620
- Wer: 36.9269
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 100
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7705 | 0.8929 | 100 | 0.4885 | 36.5551 |
| 0.7193 | 1.7857 | 200 | 0.4840 | 36.6791 |
| 0.7376 | 2.6786 | 300 | 0.4808 | 36.4312 |
| 0.6975 | 3.5714 | 400 | 0.4783 | 36.4312 |
| 0.6499 | 4.4643 | 500 | 0.4763 | 35.8116 |
| 0.7137 | 5.3571 | 600 | 0.4744 | 35.9356 |
| 0.6397 | 6.25 | 700 | 0.4727 | 35.9356 |
| 0.6441 | 7.1429 | 800 | 0.4708 | 35.9356 |
| 0.6756 | 8.0357 | 900 | 0.4690 | 35.9356 |
| 0.6331 | 8.9286 | 1000 | 0.4673 | 36.3073 |
| 0.6411 | 9.8214 | 1100 | 0.4656 | 36.3073 |
| 0.6029 | 10.7143 | 1200 | 0.4638 | 36.6791 |
| 0.6229 | 11.6071 | 1300 | 0.4620 | 36.9269 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.2.0
- Datasets 3.1.0
- Tokenizers 0.20.3