---
library_name: transformers
license: cc-by-nc-4.0
base_model: TanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-poly
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BxSD-finetuned-UCF_RGBCROP_5e6-poly_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. -->

# BxSD-finetuned-UCF_RGBCROP_5e6-poly_2

This model is a fine-tuned version of [TanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-poly](https://huggingface.co/TanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-poly) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3358
- Accuracy: 0.8056

## 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
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 345

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.5386        | 0.0696  | 24   | 0.5426          | 0.7619   |
| 0.284         | 1.0696  | 48   | 0.4675          | 0.8333   |
| 0.0153        | 2.0696  | 72   | 0.3591          | 0.9048   |
| 0.0033        | 3.0696  | 96   | 0.4866          | 0.9048   |
| 0.0014        | 4.0696  | 120  | 0.4560          | 0.9048   |
| 0.0011        | 5.0696  | 144  | 0.4384          | 0.9286   |
| 0.0009        | 6.0696  | 168  | 0.4652          | 0.9286   |
| 0.0008        | 7.0696  | 192  | 0.4820          | 0.9286   |
| 0.0007        | 8.0696  | 216  | 0.4606          | 0.9286   |
| 0.0006        | 9.0696  | 240  | 0.4676          | 0.9286   |
| 0.0006        | 10.0696 | 264  | 0.4681          | 0.9286   |
| 0.0006        | 11.0696 | 288  | 0.4760          | 0.9286   |
| 0.0005        | 12.0696 | 312  | 0.4777          | 0.9286   |
| 0.0005        | 13.0696 | 336  | 0.4788          | 0.9286   |
| 0.0006        | 14.0261 | 345  | 0.4786          | 0.9286   |


### Framework versions

- Transformers 4.52.2
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1