---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./800
  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. -->

# ./800

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the 800 SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6191
- Wer Ortho: 30.5394
- Wer: 20.0215

## 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: 3e-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: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 1.2835        | 2.0   | 100  | 0.7681          | 30.5758   | 19.3039 |
| 0.5883        | 4.0   | 200  | 0.6235          | 27.6968   | 17.5099 |
| 0.3246        | 6.0   | 300  | 0.5332          | 29.4461   | 19.6268 |
| 0.1851        | 8.0   | 400  | 0.5366          | 34.6574   | 23.3226 |
| 0.1133        | 10.0  | 500  | 0.5747          | 29.9198   | 19.0886 |
| 0.0837        | 12.0  | 600  | 0.5947          | 30.1020   | 19.9498 |
| 0.0697        | 14.0  | 700  | 0.6128          | 30.3571   | 20.4521 |
| 0.0622        | 16.0  | 800  | 0.6191          | 30.5394   | 20.0215 |


### Framework versions

- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.21.0
- Tokenizers 0.19.1