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

# openai/whisper-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1711
- Wer: 10.1446

## 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: 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: 200
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.111         | 0.2   | 1000 | 0.1786          | 11.0063 |
| 0.0961        | 1.16  | 2000 | 0.1719          | 10.5906 |
| 0.0732        | 2.12  | 3000 | 0.1743          | 10.3268 |
| 0.0742        | 3.08  | 4000 | 0.1715          | 10.2262 |
| 0.0692        | 4.03  | 5000 | 0.1711          | 10.1446 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2