metadata
base_model: openai/whisper-large-v3
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
config: default
split: train
args: default
metrics:
- type: wer
value: 100
name: Wer
Whisper Medium
This model is a fine-tuned version of openai/whisper-large-v3 on the b-brave/speech_disorders_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.1865
- Wer: 100.0
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: 48
- training_steps: 256
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.423 | 0.375 | 48 | 0.3535 | 106.0166 |
| 0.3121 | 0.75 | 96 | 0.2261 | 100.0 |
| 0.2534 | 1.125 | 144 | 0.1995 | 100.0 |
| 0.147 | 1.5 | 192 | 0.1973 | 99.7925 |
| 0.1161 | 1.875 | 240 | 0.1865 | 100.0 |
Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1