---
library_name: transformers
language:
- id
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base - FineTuned - Id -
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: id
      split: None
      args: 'config: id, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 45.61101549053356
---

<!-- 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 Base - FineTuned - Id -

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8705
- Wer: 45.6110

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.891         | 1.5873  | 100  | 0.7102          | 48.5370 |
| 0.3582        | 3.1746  | 200  | 0.7179          | 45.3528 |
| 0.1205        | 4.7619  | 300  | 0.7682          | 46.2134 |
| 0.0413        | 6.3492  | 400  | 0.7906          | 68.7608 |
| 0.0179        | 7.9365  | 500  | 0.8193          | 57.4010 |
| 0.0091        | 9.5238  | 600  | 0.8451          | 45.3528 |
| 0.0064        | 11.1111 | 700  | 0.8578          | 45.7831 |
| 0.0048        | 12.6984 | 800  | 0.8647          | 45.9552 |
| 0.0042        | 14.2857 | 900  | 0.8683          | 45.6110 |
| 0.004         | 15.8730 | 1000 | 0.8705          | 45.6110 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3