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
config: default
split: train
args: default
metrics:
- type: wer
value: 21.24248496993988
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: 0.2798
- Wer: 21.2425
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 250
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.4644 | 1.0417 | 50 | 6.2039 | 73.7475 |
| 3.2455 | 2.0833 | 100 | 0.3363 | 23.6473 |
| 0.1546 | 3.125 | 150 | 0.2708 | 20.8417 |
| 0.0685 | 4.1667 | 200 | 0.2790 | 19.8397 |
| 0.0427 | 5.2083 | 250 | 0.2798 | 21.2425 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.4
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1