---
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_alpha0.7_temp5.0_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_alpha0.7_temp5.0_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: 0.9566
- Accuracy: 0.6584

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5605        | 1.0   | 164  | 1.4026          | 0.2625   |
| 0.5309        | 2.0   | 328  | 1.3395          | 0.3210   |
| 0.4735        | 3.0   | 492  | 1.1833          | 0.4967   |
| 0.4298        | 4.0   | 656  | 1.1390          | 0.5260   |
| 0.4036        | 5.0   | 820  | 1.0785          | 0.5748   |
| 0.3936        | 6.0   | 984  | 1.0463          | 0.5922   |
| 0.3746        | 7.0   | 1148 | 1.0220          | 0.6074   |
| 0.3644        | 8.0   | 1312 | 1.0024          | 0.6312   |
| 0.3514        | 9.0   | 1476 | 0.9987          | 0.6161   |
| 0.3366        | 10.0  | 1640 | 1.0162          | 0.6247   |
| 0.3377        | 11.0  | 1804 | 1.0073          | 0.6074   |
| 0.3291        | 12.0  | 1968 | 0.9801          | 0.6323   |
| 0.3156        | 13.0  | 2132 | 0.9602          | 0.6584   |
| 0.3177        | 14.0  | 2296 | 0.9742          | 0.6443   |
| 0.31          | 15.0  | 2460 | 0.9683          | 0.6486   |
| 0.3071        | 16.0  | 2624 | 0.9692          | 0.6508   |
| 0.3077        | 17.0  | 2788 | 0.9566          | 0.6573   |
| 0.2957        | 18.0  | 2952 | 0.9566          | 0.6584   |
| 0.3017        | 19.0  | 3116 | 0.9575          | 0.6649   |
| 0.2911        | 20.0  | 3280 | 0.9593          | 0.6573   |


### Framework versions

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