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---
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
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