---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-cit-do0.15-wd0.0001
  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-do0.15-wd0.0001

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: 0.6948
- Wer: 34.0961

## 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: 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.1267        | 0.8889  | 10   | 1.1143          | 48.9703 |
| 1.0883        | 1.7778  | 20   | 1.0068          | 40.0458 |
| 0.9315        | 2.6667  | 30   | 0.8667          | 38.9016 |
| 0.751         | 3.5556  | 40   | 0.7886          | 34.0961 |
| 0.6968        | 4.4444  | 50   | 0.7158          | 35.0114 |
| 0.5946        | 5.3333  | 60   | 0.6504          | 31.8078 |
| 0.5011        | 6.2222  | 70   | 0.6133          | 31.3501 |
| 0.4061        | 7.1111  | 80   | 0.5869          | 33.6384 |
| 0.3731        | 8.0     | 90   | 0.5718          | 32.9519 |
| 0.2977        | 8.8889  | 100  | 0.5688          | 33.1808 |
| 0.2612        | 9.7778  | 110  | 0.5742          | 32.9519 |
| 0.2105        | 10.6667 | 120  | 0.5845          | 32.2654 |
| 0.1775        | 11.5556 | 130  | 0.5981          | 32.7231 |
| 0.1479        | 12.4444 | 140  | 0.6118          | 31.1213 |
| 0.1173        | 13.3333 | 150  | 0.6255          | 33.1808 |
| 0.111         | 14.2222 | 160  | 0.6426          | 35.4691 |
| 0.0946        | 15.1111 | 170  | 0.6641          | 34.5538 |
| 0.0799        | 16.0    | 180  | 0.6772          | 34.7826 |
| 0.0739        | 16.8889 | 190  | 0.6904          | 34.0961 |
| 0.0682        | 17.7778 | 200  | 0.6948          | 34.0961 |


### Framework versions

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