---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium.en
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-medium.en

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on an [acc_dataset_v3](https://huggingface.co/datasets/monadical-labs/acc_dataset_v3) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4242
- Wer: 0.1293

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

See the training notebook [here](https://huggingface.co/monadical-labs/whisper-medium.en/blob/main/Finetuning-notebook-whisper-on-acc-data.ipynb): 

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 4
- seed: 42
- 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: 25
- training_steps: 300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 1.6045        | 2.2727  | 25   | 0.9047          | 0.1535 |
| 0.2267        | 4.5455  | 50   | 0.4149          | 0.1262 |
| 0.0207        | 6.8182  | 75   | 0.4454          | 0.1483 |
| 0.0134        | 9.0909  | 100  | 0.4660          | 0.1388 |
| 0.009         | 11.3636 | 125  | 0.4311          | 0.1462 |
| 0.0051        | 13.6364 | 150  | 0.4368          | 0.1356 |
| 0.0018        | 15.9091 | 175  | 0.4294          | 0.1462 |
| 0.0003        | 18.1818 | 200  | 0.4234          | 0.1356 |
| 0.0002        | 20.4545 | 225  | 0.4235          | 0.1325 |
| 0.0002        | 22.7273 | 250  | 0.4239          | 0.1304 |
| 0.0002        | 25.0    | 275  | 0.4240          | 0.1283 |
| 0.0002        | 27.2727 | 300  | 0.4242          | 0.1293 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0