---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-finetuned-2
  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-v3-finetuned-2

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: 1.8292
- Wer: 29.2595

## 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-09
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 1.0224        | 1.0   | 7532  | 1.8944          | 30.6810 |
| 2.932         | 2.0   | 15064 | 1.8575          | 30.1652 |
| 1.6702        | 3.0   | 22596 | 1.8380          | 29.3775 |
| 1.9191        | 4.0   | 30128 | 1.8304          | 29.2800 |
| 2.155         | 5.0   | 37660 | 1.8292          | 29.2595 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2