---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: fs-w-xavier-base
  results: []
---

<!-- 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. -->

# fs-w-xavier-base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3748
- Wer: 90.8832
- Cer: 69.2460

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      | Cer     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------:|
| 3.8293        | 4.5872  | 500  | 3.9014          | 98.4330  | 73.8234 |
| 0.9253        | 9.1743  | 1000 | 1.1787          | 101.2821 | 77.9887 |
| 0.3997        | 13.7615 | 1500 | 0.6684          | 98.9079  | 76.8980 |
| 0.3313        | 18.3486 | 2000 | 0.4931          | 97.4359  | 79.5259 |
| 0.2974        | 22.9358 | 2500 | 0.4656          | 109.0693 | 83.0385 |
| 0.2635        | 27.5229 | 3000 | 0.4219          | 103.5138 | 78.6843 |
| 0.2241        | 32.1101 | 3500 | 0.4047          | 100.5698 | 77.2587 |
| 0.1939        | 36.6972 | 4000 | 0.3893          | 89.9810  | 69.3404 |
| 0.1718        | 41.2844 | 4500 | 0.3807          | 87.8443  | 67.3738 |
| 0.1471        | 45.8716 | 5000 | 0.3748          | 90.8832  | 69.2460 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0