---
library_name: peft
language:
- it
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- easycall-v2-disordersvoice
metrics:
- wer
model-index:
- name: Whisper Medium
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: easycall-v2-disordersvoice
      type: easycall-v2-disordersvoice
      split: None
    metrics:
    - type: wer
      value: 18.95910780669145
      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 [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the easycall-v2-disordersvoice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2372
- Wer: 18.9591

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adafactor and the args are:
No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log        | 1.0   | 151  | 0.3071          | 39.0335 |
| No log        | 2.0   | 302  | 0.2418          | 20.0743 |
| No log        | 3.0   | 453  | 0.2288          | 18.0917 |
| 0.3944        | 4.0   | 604  | 0.2240          | 19.0830 |
| 0.3944        | 5.0   | 755  | 0.2298          | 17.5960 |
| 0.3944        | 6.0   | 906  | 0.2339          | 18.8352 |
| 0.0257        | 7.0   | 1057 | 0.2372          | 18.9591 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.2
- Tokenizers 0.21.0