---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./200
  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. -->

# ./200

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the 200 SF 200 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8389
- Wer Ortho: 35.1676
- Wer: 23.8967

## 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: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 1.5629        | 8.0   | 100  | 1.1016          | 41.3994   | 29.9964 |
| 0.7012        | 16.0  | 200  | 0.8286          | 36.0787   | 25.1525 |
| 0.4369        | 24.0  | 300  | 0.8091          | 36.1152   | 25.3678 |
| 0.3073        | 32.0  | 400  | 0.8257          | 34.7303   | 23.7890 |
| 0.2298        | 40.0  | 500  | 0.8354          | 34.8397   | 22.8920 |
| 0.1938        | 48.0  | 600  | 0.8306          | 35.4592   | 23.4661 |
| 0.1658        | 56.0  | 700  | 0.8359          | 35.5321   | 23.8967 |
| 0.1534        | 64.0  | 800  | 0.8389          | 35.1676   | 23.8967 |


### Framework versions

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