---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./400
  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. -->

# ./400

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the 400 SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7217
- Wer Ortho: 29.6283
- Wer: 19.5551

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 1.6015        | 4.0   | 100  | 1.1045          | 41.2901   | 30.3911 |
| 0.8237        | 8.0   | 200  | 0.7959          | 31.3776   | 20.4880 |
| 0.5824        | 12.0  | 300  | 0.7417          | 29.7741   | 19.3757 |
| 0.4724        | 16.0  | 400  | 0.7256          | 29.5554   | 19.4474 |
| 0.4232        | 20.0  | 500  | 0.7217          | 29.6283   | 19.5551 |


### Framework versions

- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1