metadata
library_name: peft
language:
- it
base_model: b-brave/asr_double_training_15-10-2024_merged
tags:
- generated_from_trainer
datasets:
- b-brave/speech_disorders_voice_edit
metrics:
- wer
model-index:
- name: Whisper Medium
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: b-brave/speech_disorders_voice_edit
type: b-brave/speech_disorders_voice_edit
config: default
split: test
args: default
metrics:
- type: wer
value: 37.05080545229244
name: Wer
Whisper Medium
This model is a fine-tuned version of b-brave/asr_double_training_15-10-2024_merged on the b-brave/speech_disorders_voice_edit dataset. It achieves the following results on the evaluation set:
- Loss: 0.4433
- Wer: 37.0508
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 150
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1148 | 1.3245 | 100 | 0.4660 | 36.0595 |
| 0.0889 | 2.6490 | 200 | 0.4470 | 39.0335 |
| 0.0689 | 3.9735 | 300 | 0.4346 | 36.1834 |
| 0.0424 | 5.2980 | 400 | 0.4367 | 36.0595 |
| 0.0288 | 6.6225 | 500 | 0.4420 | 36.3073 |
| 0.0273 | 7.9470 | 600 | 0.4433 | 37.0508 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.2.0
- Datasets 3.1.0
- Tokenizers 0.20.3