---
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: medium
  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. -->

# medium

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6406
- Wer: 10.0661
- Cer: 6.1253
- Wer Normalized: 10.0637

## 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: 32
- eval_batch_size: 16
- 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: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer    | Wer Normalized |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:--------------:|
| 0.4967        | 1.75  | 500  | 0.3843          | 9.3314  | 5.5994 | 9.3264         |
| 0.1883        | 3.51  | 1000 | 0.4699          | 9.8026  | 5.9139 | 9.7977         |
| 0.058         | 5.26  | 1500 | 0.6406          | 10.0661 | 6.1253 | 10.0637        |


### Framework versions

- Transformers 4.39.3
- Pytorch 1.12.1+cu116
- Datasets 2.18.0
- Tokenizers 0.15.2