---
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: 36.926889714993806
      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: 0.4620
- Wer: 36.9269

## 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: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 100
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.7705        | 0.8929  | 100  | 0.4885          | 36.5551 |
| 0.7193        | 1.7857  | 200  | 0.4840          | 36.6791 |
| 0.7376        | 2.6786  | 300  | 0.4808          | 36.4312 |
| 0.6975        | 3.5714  | 400  | 0.4783          | 36.4312 |
| 0.6499        | 4.4643  | 500  | 0.4763          | 35.8116 |
| 0.7137        | 5.3571  | 600  | 0.4744          | 35.9356 |
| 0.6397        | 6.25    | 700  | 0.4727          | 35.9356 |
| 0.6441        | 7.1429  | 800  | 0.4708          | 35.9356 |
| 0.6756        | 8.0357  | 900  | 0.4690          | 35.9356 |
| 0.6331        | 8.9286  | 1000 | 0.4673          | 36.3073 |
| 0.6411        | 9.8214  | 1100 | 0.4656          | 36.3073 |
| 0.6029        | 10.7143 | 1200 | 0.4638          | 36.6791 |
| 0.6229        | 11.6071 | 1300 | 0.4620          | 36.9269 |


### Framework versions

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