---
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: 0.1334
- Wer: 6.9935

## 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-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
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5784        | 0.4   | 100  | 0.3881          | 20.8915 |
| 0.2412        | 0.8   | 200  | 0.2176          | 12.1310 |
| 0.1962        | 1.2   | 300  | 0.1909          | 10.6681 |
| 0.182         | 1.6   | 400  | 0.1782          | 9.7530  |
| 0.1683        | 2.0   | 500  | 0.1697          | 8.9785  |
| 0.1418        | 2.4   | 600  | 0.1639          | 8.9699  |
| 0.1605        | 2.8   | 700  | 0.1590          | 8.4593  |
| 0.13          | 3.2   | 800  | 0.1550          | 7.9774  |
| 0.1353        | 3.6   | 900  | 0.1518          | 7.7623  |
| 0.13          | 4.0   | 1000 | 0.1491          | 7.4897  |
| 0.1288        | 4.4   | 1100 | 0.1467          | 7.4897  |
| 0.12          | 4.8   | 1200 | 0.1448          | 7.4180  |
| 0.1161        | 5.2   | 1300 | 0.1428          | 7.3807  |
| 0.113         | 5.6   | 1400 | 0.1414          | 7.5356  |
| 0.1022        | 6.0   | 1500 | 0.1399          | 6.9505  |
| 0.1029        | 6.4   | 1600 | 0.1390          | 6.9361  |
| 0.0981        | 6.8   | 1700 | 0.1379          | 6.8070  |
| 0.1051        | 7.2   | 1800 | 0.1369          | 6.8357  |
| 0.0927        | 7.6   | 1900 | 0.1362          | 6.8988  |
| 0.0973        | 8.0   | 2000 | 0.1354          | 6.8042  |
| 0.0898        | 8.4   | 2100 | 0.1348          | 6.7497  |
| 0.0929        | 8.8   | 2200 | 0.1342          | 6.7870  |
| 0.0937        | 9.2   | 2300 | 0.1338          | 7.0623  |
| 0.0901        | 9.6   | 2400 | 0.1334          | 6.9935  |


### Framework versions

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