---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-try1
  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-try1

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4609
- Wer: 0.4140

## 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: 1
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0744        | 14.2857 | 200  | 1.2271          | 0.3814 |
| 0.0251        | 28.5714 | 400  | 1.2939          | 0.3907 |
| 0.0088        | 42.8571 | 600  | 1.3904          | 0.4047 |
| 0.004         | 57.1429 | 800  | 1.4430          | 0.4140 |
| 0.0031        | 71.4286 | 1000 | 1.4609          | 0.4140 |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1