---
library_name: transformers
license: apache-2.0
base_model: c14kevincardenas/ClimBEiT-t3
tags:
- knowledge_distillation
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilevit-small_alpha0.5_temp3.0_t3
  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. -->

# mobilevit-small_alpha0.5_temp3.0_t3

This model is a fine-tuned version of [c14kevincardenas/ClimBEiT-t3](https://huggingface.co/c14kevincardenas/ClimBEiT-t3) on the c14kevincardenas/beta_caller_284_person_crop_seq_withlimb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8562
- Accuracy: 0.7072

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8034        | 1.0   | 164  | 1.3824          | 0.2863   |
| 0.7605        | 2.0   | 328  | 1.3374          | 0.2918   |
| 0.6903        | 3.0   | 492  | 1.1406          | 0.5152   |
| 0.6045        | 4.0   | 656  | 1.0571          | 0.5629   |
| 0.5779        | 5.0   | 820  | 1.0227          | 0.5813   |
| 0.5423        | 6.0   | 984  | 0.9594          | 0.6334   |
| 0.5154        | 7.0   | 1148 | 0.9498          | 0.6518   |
| 0.4984        | 8.0   | 1312 | 0.9111          | 0.6757   |
| 0.47          | 9.0   | 1476 | 0.9155          | 0.6518   |
| 0.4474        | 10.0  | 1640 | 0.9253          | 0.6518   |
| 0.4547        | 11.0  | 1804 | 0.9355          | 0.6562   |
| 0.4432        | 12.0  | 1968 | 0.8718          | 0.6649   |
| 0.4235        | 13.0  | 2132 | 0.8763          | 0.7039   |
| 0.419         | 14.0  | 2296 | 0.8878          | 0.6866   |
| 0.4083        | 15.0  | 2460 | 0.8869          | 0.6898   |
| 0.4043        | 16.0  | 2624 | 0.8697          | 0.6985   |
| 0.4061        | 17.0  | 2788 | 0.8562          | 0.7072   |
| 0.389         | 18.0  | 2952 | 0.8595          | 0.7082   |
| 0.3982        | 19.0  | 3116 | 0.8661          | 0.6985   |
| 0.3823        | 20.0  | 3280 | 0.8689          | 0.7115   |


### Framework versions

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