metadata
base_model: openai/whisper-medium
datasets:
- b-brave/speech_disorders_voice
language:
- it
library_name: peft
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper Medium
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: b-brave/speech_disorders_voice
type: b-brave/speech_disorders_voice
split: None
metrics:
- type: wer
value: 46.04051565377532
name: Wer
Whisper Medium
This model is a fine-tuned version of openai/whisper-medium on the b-brave/speech_disorders_voice dataset. It achieves the following results on the evaluation set:
- Loss: 4.0226
- Wer: 46.0405
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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
3.6195 | 0.0149 | 2 | 4.8117 | 55.4328 |
5.431 | 0.0299 | 4 | 4.0226 | 46.0405 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1