---
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-do0.15-wd0-lr1e-05
  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-do0.15-wd0-lr1e-05

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the SF 200 synth 2000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3455
- Wer: 15.0359

## 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-05
- 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: 300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5226        | 0.4040 | 50   | 0.3027          | 17.5235 |
| 0.2202        | 0.8081 | 100  | 0.2734          | 16.6022 |
| 0.1105        | 1.2121 | 150  | 0.2876          | 16.1047 |
| 0.0613        | 1.6162 | 200  | 0.2642          | 14.3542 |
| 0.0504        | 2.0202 | 250  | 0.3025          | 14.3910 |
| 0.0158        | 2.4242 | 300  | 0.3455          | 15.0359 |


### Framework versions

- Transformers 4.41.2
- Pytorch 1.13.1+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1