---
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_temp3.0_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_temp3.0_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: 0.4847
- Accuracy: 0.8379

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2201        | 1.0   | 180  | 1.3453          | 0.3804   |
| 0.7455        | 2.0   | 360  | 0.8167          | 0.6897   |
| 0.5498        | 3.0   | 540  | 0.6835          | 0.7609   |
| 0.4331        | 4.0   | 720  | 0.6307          | 0.7737   |
| 0.3415        | 5.0   | 900  | 0.5956          | 0.7915   |
| 0.2533        | 6.0   | 1080 | 0.5516          | 0.8113   |
| 0.2366        | 7.0   | 1260 | 0.5602          | 0.8073   |
| 0.2326        | 8.0   | 1440 | 0.6457          | 0.7866   |
| 0.2331        | 9.0   | 1620 | 0.5528          | 0.8024   |
| 0.2284        | 10.0  | 1800 | 0.5510          | 0.8083   |
| 0.1929        | 11.0  | 1980 | 0.5410          | 0.8152   |
| 0.1819        | 12.0  | 2160 | 0.5152          | 0.8251   |
| 0.1677        | 13.0  | 2340 | 0.5095          | 0.8192   |
| 0.1647        | 14.0  | 2520 | 0.4979          | 0.8310   |
| 0.1669        | 15.0  | 2700 | 0.5143          | 0.8370   |
| 0.1511        | 16.0  | 2880 | 0.4890          | 0.8449   |
| 0.1523        | 17.0  | 3060 | 0.4996          | 0.8360   |
| 0.1562        | 18.0  | 3240 | 0.4913          | 0.8350   |
| 0.1474        | 19.0  | 3420 | 0.4876          | 0.8379   |
| 0.1422        | 20.0  | 3600 | 0.4847          | 0.8379   |


### Framework versions

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