---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
model-index:
- name: uaspeech-large-finetune-long-evals-30-11-11AM
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/neuronbit-tech/finetune_uaspeech_wandb_long_evals_30_11_11AM/runs/ce0ctgl5)
# uaspeech-large-finetune-long-evals-30-11-11AM

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: 0.3481

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 5000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.2252        | 0.2070 | 500  | 0.3504          |
| 0.1217        | 0.4139 | 1000 | 0.3028          |
| 0.071         | 0.6209 | 1500 | 0.3409          |
| 0.0581        | 0.8278 | 2000 | 0.3390          |
| 0.0279        | 1.0348 | 2500 | 0.3261          |
| 0.0132        | 1.2417 | 3000 | 0.3258          |
| 0.006         | 1.4487 | 3500 | 0.3280          |
| 0.0077        | 1.6556 | 4000 | 0.3553          |
| 0.0094        | 1.8626 | 4500 | 0.3516          |
| 0.0043        | 2.0695 | 5000 | 0.3481          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3