---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-ft-5000
  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-ft-5000

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2673
- Wer: 10.3673

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5238        | 1.0   | 313  | 0.2389          | 12.2734 |
| 0.1035        | 2.0   | 626  | 0.2360          | 11.2041 |
| 0.0381        | 3.0   | 939  | 0.2349          | 10.7857 |
| 0.0134        | 4.0   | 1252 | 0.2512          | 10.5532 |
| 0.0039        | 5.0   | 1565 | 0.2611          | 10.2278 |
| 0.0013        | 6.0   | 1878 | 0.2673          | 10.3673 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3