---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-en
  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-en

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: 0.1362
- Wer: 4.3516

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 50
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0146        | 0.4   | 100  | 0.1223          | 4.8708 |
| 0.0159        | 0.8   | 200  | 0.1248          | 4.8306 |
| 0.0104        | 1.2   | 300  | 0.1251          | 4.3803 |
| 0.01          | 1.6   | 400  | 0.1259          | 4.3975 |
| 0.0092        | 2.0   | 500  | 0.1263          | 4.4749 |
| 0.0055        | 2.4   | 600  | 0.1301          | 4.3344 |
| 0.0062        | 2.8   | 700  | 0.1303          | 4.4061 |
| 0.0039        | 3.2   | 800  | 0.1324          | 4.5294 |
| 0.0045        | 3.6   | 900  | 0.1337          | 4.3889 |
| 0.0036        | 4.0   | 1000 | 0.1350          | 4.2626 |
| 0.0033        | 4.4   | 1100 | 0.1358          | 4.3344 |
| 0.0033        | 4.8   | 1200 | 0.1362          | 4.3516 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3