---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./whisper-large-cit-synth-do015-wd0-lr5e-06-1000
  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-synth-do015-wd0-lr5e-06-1000

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4526
- Wer: 20.3899

## 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: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7187        | 0.8889 | 50   | 0.4062          | 24.2105 |
| 0.4122        | 1.7778 | 100  | 0.3523          | 22.3782 |
| 0.2917        | 2.6667 | 150  | 0.3494          | 23.5867 |
| 0.2242        | 3.5556 | 200  | 0.3618          | 23.0019 |
| 0.1529        | 4.4444 | 250  | 0.3770          | 22.3392 |
| 0.1322        | 5.3333 | 300  | 0.3906          | 21.2476 |
| 0.0987        | 6.2222 | 350  | 0.4133          | 20.9747 |
| 0.0798        | 7.1111 | 400  | 0.4302          | 23.8986 |
| 0.0613        | 8.0    | 450  | 0.4438          | 20.5848 |
| 0.0545        | 8.8889 | 500  | 0.4526          | 20.3899 |


### Framework versions

- Transformers 4.42.3
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1