---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./300
  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. -->

# ./300

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the 300 SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.75
- Wer Ortho: 33.0175
- Wer: 21.3491

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 1.6187        | 5.2632  | 100  | 1.1230          | 41.5087   | 30.1041 |
| 0.7964        | 10.5263 | 200  | 0.8076          | 31.8878   | 20.2368 |
| 0.5424        | 15.7895 | 300  | 0.7627          | 31.7055   | 20.0933 |
| 0.4204        | 21.0526 | 400  | 0.7495          | 33.1268   | 21.2056 |
| 0.3666        | 26.3158 | 500  | 0.75            | 33.0175   | 21.3491 |


### Framework versions

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