---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-cit-do0.2-wd0.001-tr5
  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. -->

# whisper-large-cit-do0.2-wd0.001-tr5

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the SF 200 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8701
- Wer: 28.8330

## 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: 5e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- 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: 100
- training_steps: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.0205        | 0.8889  | 10   | 0.8452          | 34.3249 |
| 0.7299        | 1.7778  | 20   | 0.6455          | 31.1213 |
| 0.48          | 2.6667  | 30   | 0.5552          | 30.4348 |
| 0.291         | 3.5556  | 40   | 0.5288          | 30.6636 |
| 0.1931        | 4.4444  | 50   | 0.5479          | 28.3753 |
| 0.107         | 5.3333  | 60   | 0.6104          | 29.0618 |
| 0.0622        | 6.2222  | 70   | 0.6509          | 28.8330 |
| 0.0271        | 7.1111  | 80   | 0.7900          | 30.4348 |
| 0.0198        | 8.0     | 90   | 0.7246          | 30.2059 |
| 0.0176        | 8.8889  | 100  | 0.6992          | 27.6888 |
| 0.0163        | 9.7778  | 110  | 0.7896          | 29.5195 |
| 0.0087        | 10.6667 | 120  | 0.7793          | 30.4348 |
| 0.0092        | 11.5556 | 130  | 0.8213          | 28.8330 |
| 0.0063        | 12.4444 | 140  | 0.8369          | 29.5195 |
| 0.0038        | 13.3333 | 150  | 0.8262          | 29.7483 |
| 0.0036        | 14.2222 | 160  | 0.8506          | 28.3753 |
| 0.0021        | 15.1111 | 170  | 0.8647          | 29.5195 |
| 0.0017        | 16.0    | 180  | 0.8608          | 29.5195 |
| 0.0012        | 16.8889 | 190  | 0.8662          | 28.8330 |
| 0.001         | 17.7778 | 200  | 0.8701          | 28.8330 |


### Framework versions

- Transformers 4.41.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1