---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
model-index:
- name: uaspeech-large-finetune-shorter-evals-29-11-8AM
  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_shorter_evals_29_11_8AM/runs/j3agl8d1)
# uaspeech-large-finetune-shorter-evals-29-11-8AM

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: 0.2763

## 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: 100
- training_steps: 1500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3168        | 0.0828 | 200  | 0.3934          |
| 0.2478        | 0.1242 | 300  | 0.3321          |
| 0.2151        | 0.1656 | 400  | 0.3295          |
| 0.1683        | 0.2070 | 500  | 0.3064          |
| 0.1469        | 0.2483 | 600  | 0.3344          |
| 0.1183        | 0.2897 | 700  | 0.2818          |
| 0.0982        | 0.3311 | 800  | 0.2951          |
| 0.1028        | 0.3725 | 900  | 0.2737          |
| 0.0901        | 0.4139 | 1000 | 0.2723          |
| 0.0724        | 0.4553 | 1100 | 0.2761          |
| 0.0668        | 0.4967 | 1200 | 0.2807          |
| 0.0641        | 0.5381 | 1300 | 0.2699          |
| 0.041         | 0.5795 | 1400 | 0.2727          |
| 0.0438        | 0.6209 | 1500 | 0.2763          |


### Framework versions

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