---
library_name: transformers
license: apache-2.0
base_model: c14kevincardenas/ClimBEiT-t2
tags:
- knowledge_distillation
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beit-base-finetuned-ade-640-640_alpha0.5_temp5.0_t2
  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. -->

# beit-base-finetuned-ade-640-640_alpha0.5_temp5.0_t2

This model is a fine-tuned version of [c14kevincardenas/ClimBEiT-t2](https://huggingface.co/c14kevincardenas/ClimBEiT-t2) on the c14kevincardenas/beta_caller_284_person_crop_seq_withlimb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4849
- Accuracy: 0.8389

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1929        | 1.0   | 180  | 1.3065          | 0.3972   |
| 0.7186        | 2.0   | 360  | 0.8221          | 0.6917   |
| 0.5468        | 3.0   | 540  | 0.7486          | 0.7223   |
| 0.4245        | 4.0   | 720  | 0.6552          | 0.7688   |
| 0.3503        | 5.0   | 900  | 0.5798          | 0.7945   |
| 0.2533        | 6.0   | 1080 | 0.6044          | 0.7875   |
| 0.2419        | 7.0   | 1260 | 0.5754          | 0.8014   |
| 0.238         | 8.0   | 1440 | 0.6908          | 0.7727   |
| 0.2325        | 9.0   | 1620 | 0.5579          | 0.8063   |
| 0.2118        | 10.0  | 1800 | 0.5279          | 0.8261   |
| 0.1827        | 11.0  | 1980 | 0.5354          | 0.8182   |
| 0.1797        | 12.0  | 2160 | 0.5396          | 0.8310   |
| 0.1628        | 13.0  | 2340 | 0.5208          | 0.8350   |
| 0.1628        | 14.0  | 2520 | 0.5148          | 0.8182   |
| 0.1613        | 15.0  | 2700 | 0.5173          | 0.8162   |
| 0.151         | 16.0  | 2880 | 0.4949          | 0.8320   |
| 0.1492        | 17.0  | 3060 | 0.5020          | 0.8281   |
| 0.1538        | 18.0  | 3240 | 0.4889          | 0.8281   |
| 0.1434        | 19.0  | 3420 | 0.4910          | 0.8350   |
| 0.1391        | 20.0  | 3600 | 0.4849          | 0.8389   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1