---
library_name: peft
language:
- it
base_model: b-brave/asr_double_training_15-10-2024_merged
tags:
- generated_from_trainer
datasets:
- ASR_BB_and_EC
metrics:
- wer
model-index:
- name: Whisper Medium
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: ASR_BB_and_EC
      type: ASR_BB_and_EC
      config: default
      split: test
      args: default
    metrics:
    - type: wer
      value: 36.18339529120198
      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 ASR_BB_and_EC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4690
- Wer: 36.1834

## 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: 1e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.9758        | 0.5464 | 50   | 0.4882          | 36.5551 |
| 0.81          | 1.0929 | 100  | 0.4839          | 36.5551 |
| 0.8005        | 1.6393 | 150  | 0.4808          | 36.4312 |
| 0.8837        | 2.1858 | 200  | 0.4782          | 35.8116 |
| 0.8172        | 2.7322 | 250  | 0.4760          | 35.8116 |
| 0.7142        | 3.2787 | 300  | 0.4742          | 35.9356 |
| 0.7817        | 3.8251 | 350  | 0.4724          | 35.9356 |
| 0.8025        | 4.3716 | 400  | 0.4707          | 36.0595 |
| 0.782         | 4.9180 | 450  | 0.4690          | 36.1834 |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.2.0
- Datasets 3.1.0
- Tokenizers 0.20.3