---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-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. -->

# whisper-base

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: 0.2522
- Wer: 23.1797

## 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: 64
- eval_batch_size: 64
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 2.1114        | 0.0   | 1     | 2.3698          | 75.1864 |
| 0.3272        | 0.29  | 1000  | 0.4182          | 37.7505 |
| 0.251         | 0.58  | 2000  | 0.3408          | 30.9679 |
| 0.2207        | 0.88  | 3000  | 0.3059          | 28.3058 |
| 0.1779        | 1.17  | 4000  | 0.2890          | 26.7555 |
| 0.1691        | 1.46  | 5000  | 0.2742          | 25.2099 |
| 0.1622        | 1.75  | 6000  | 0.2645          | 24.6840 |
| 0.1397        | 2.04  | 7000  | 0.2587          | 23.8812 |
| 0.1394        | 2.34  | 8000  | 0.2562          | 23.6586 |
| 0.1361        | 2.63  | 9000  | 0.2536          | 23.4633 |
| 0.1356        | 2.92  | 10000 | 0.2522          | 23.1797 |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.3