---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- fsicoli/common_voice_18_0
metrics:
- wer
model-index:
- name: Whisper Medium New Train
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 18.0
      type: fsicoli/common_voice_18_0
    metrics:
    - name: Wer
      type: wer
      value: 2.2782892974889872
---

<!-- 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 New Train

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 18.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0204
- Wer: 2.2783

## 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-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2733        | 0.4077 | 1000 | 0.2585          | 32.5924 |
| 0.1527        | 0.8153 | 2000 | 0.1246          | 16.7238 |
| 0.0655        | 1.2230 | 3000 | 0.0776          | 10.5668 |
| 0.0455        | 1.6307 | 4000 | 0.0514          | 6.7675  |
| 0.0162        | 2.0383 | 5000 | 0.0353          | 4.4772  |
| 0.0129        | 2.4460 | 6000 | 0.0274          | 3.4364  |
| 0.0117        | 2.8536 | 7000 | 0.0220          | 2.5110  |
| 0.0044        | 3.2613 | 8000 | 0.0204          | 2.2783  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1
- Datasets 3.0.0
- Tokenizers 0.19.1