---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-baset
  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. -->

# whisper-baset

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Wer: 1.9802

## 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: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 100.0  | 100  | 0.0009          | 1.9802 |
| No log        | 200.0  | 200  | 0.0003          | 1.9802 |
| No log        | 300.0  | 300  | 0.0002          | 1.9802 |
| No log        | 400.0  | 400  | 0.0001          | 1.9802 |
| 0.0555        | 500.0  | 500  | 0.0001          | 1.9802 |
| 0.0555        | 600.0  | 600  | 0.0001          | 1.9802 |
| 0.0555        | 700.0  | 700  | 0.0001          | 1.9802 |
| 0.0555        | 800.0  | 800  | 0.0001          | 1.9802 |
| 0.0555        | 900.0  | 900  | 0.0001          | 1.9802 |
| 0.0001        | 1000.0 | 1000 | 0.0001          | 1.9802 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1