---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium.en-decoder-layernorm-english-accent
  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-medium.en-decoder-layernorm-english-accent

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the westbrook/English_Accent_DataSet dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1130
- Wer: 0.1202

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.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: 0.05
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0      | 0    | 1.3238          | 0.1256 |
| 1.3097        | 0.1270 | 200  | 1.3095          | 0.1254 |
| 1.2627        | 0.2541 | 400  | 1.2871          | 0.1238 |
| 1.2548        | 0.3811 | 600  | 1.2666          | 0.1236 |
| 1.1832        | 0.5082 | 800  | 1.2468          | 0.1233 |
| 1.1767        | 0.6352 | 1000 | 1.2284          | 0.1228 |
| 1.2110        | 0.7623 | 1200 | 1.2111          | 0.1233 |
| 1.1878        | 0.8893 | 1400 | 1.1948          | 0.1235 |
| 1.1267        | 1.0159 | 1600 | 1.1796          | 0.1237 |
| 1.1965        | 1.1429 | 1800 | 1.1652          | 0.1236 |
| 1.0833        | 1.2700 | 2000 | 1.1519          | 0.1228 |
| 1.1211        | 1.3970 | 2200 | 1.1403          | 0.1225 |
| 1.0462        | 1.5241 | 2400 | 1.1303          | 0.1225 |
| 1.1257        | 1.6511 | 2600 | 1.1220          | 0.1204 |
| 1.1305        | 1.7781 | 2800 | 1.1163          | 0.1205 |
| 1.0701        | 1.9052 | 3000 | 1.1130          | 0.1202 |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2