---
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
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper Medium

This model is a fine-tuned version of [b-brave/asr_double_training_15-10-2024_merged](https://huggingface.co/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