---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-cit-do1.5-wd1e-3-lr3
  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-do1.5-wd1e-3-lr3

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: 0.9438
- Wer: 33.1808

## 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: 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.087         | 0.8889  | 10   | 0.9839          | 39.8169 |
| 0.8784        | 1.7778  | 20   | 0.7808          | 34.3249 |
| 0.6585        | 2.6667  | 30   | 0.6338          | 32.2654 |
| 0.435         | 3.5556  | 40   | 0.5815          | 33.8673 |
| 0.3445        | 4.4444  | 50   | 0.5508          | 31.8078 |
| 0.2314        | 5.3333  | 60   | 0.5571          | 30.4348 |
| 0.1603        | 6.2222  | 70   | 0.5791          | 30.4348 |
| 0.0927        | 7.1111  | 80   | 0.6309          | 29.5195 |
| 0.0611        | 8.0     | 90   | 0.6768          | 32.7231 |
| 0.0366        | 8.8889  | 100  | 0.7544          | 29.7483 |
| 0.0199        | 9.7778  | 110  | 0.8286          | 30.8924 |
| 0.0155        | 10.6667 | 120  | 0.7920          | 29.5195 |
| 0.0066        | 11.5556 | 130  | 0.8726          | 30.2059 |
| 0.0054        | 12.4444 | 140  | 0.8955          | 31.3501 |
| 0.0077        | 13.3333 | 150  | 0.9194          | 32.0366 |
| 0.0076        | 14.2222 | 160  | 0.9336          | 32.4943 |
| 0.0021        | 15.1111 | 170  | 0.9399          | 33.1808 |
| 0.002         | 16.0    | 180  | 0.9404          | 32.2654 |
| 0.003         | 16.8889 | 190  | 0.9399          | 32.9519 |
| 0.0018        | 17.7778 | 200  | 0.9438          | 33.1808 |


### Framework versions

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