---
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-06
  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-06

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: 1.5469
- Wer: 52.8152

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 2.3143        | 0.0808 | 10   | 2.3730          | 62.3073 |
| 2.3217        | 0.1616 | 20   | 2.2910          | 60.9606 |
| 2.4278        | 0.2424 | 30   | 2.1875          | 59.9059 |
| 2.0697        | 0.3232 | 40   | 2.1152          | 59.2082 |
| 1.9675        | 0.4040 | 50   | 2.0410          | 59.1270 |
| 1.891         | 0.4848 | 60   | 1.9668          | 57.3098 |
| 1.7818        | 0.5657 | 70   | 1.8887          | 56.4660 |
| 1.7774        | 0.6465 | 80   | 1.8145          | 55.1030 |
| 1.8454        | 0.7273 | 90   | 1.7588          | 53.7238 |
| 1.6584        | 0.8081 | 100  | 1.7129          | 53.0586 |
| 2.0202        | 0.8889 | 110  | 1.6738          | 52.4258 |
| 1.6375        | 0.9697 | 120  | 1.6416          | 51.9552 |
| 1.3514        | 1.0505 | 130  | 1.6172          | 51.6307 |
| 1.5016        | 1.1313 | 140  | 1.5977          | 51.1601 |
| 1.8013        | 1.2121 | 150  | 1.5811          | 50.9330 |
| 1.4723        | 1.2929 | 160  | 1.5693          | 52.9937 |
| 1.5952        | 1.3737 | 170  | 1.5605          | 52.8152 |
| 1.4724        | 1.4545 | 180  | 1.5527          | 52.8476 |
| 1.4115        | 1.5354 | 190  | 1.5488          | 52.7990 |
| 1.5161        | 1.6162 | 200  | 1.5469          | 52.8152 |


### Framework versions

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