---
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_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_alpha0.7_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: 0.9566
- Accuracy: 0.6616

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5602        | 1.0   | 164  | 1.4016          | 0.2636   |
| 0.5293        | 2.0   | 328  | 1.3396          | 0.3178   |
| 0.4722        | 3.0   | 492  | 1.1894          | 0.4740   |
| 0.4285        | 4.0   | 656  | 1.1300          | 0.5336   |
| 0.4026        | 5.0   | 820  | 1.0758          | 0.5824   |
| 0.3918        | 6.0   | 984  | 1.0470          | 0.5900   |
| 0.3733        | 7.0   | 1148 | 1.0198          | 0.6095   |
| 0.3622        | 8.0   | 1312 | 0.9975          | 0.6356   |
| 0.3504        | 9.0   | 1476 | 0.9980          | 0.6052   |
| 0.3345        | 10.0  | 1640 | 1.0102          | 0.6171   |
| 0.3362        | 11.0  | 1804 | 1.0125          | 0.6009   |
| 0.3281        | 12.0  | 1968 | 0.9796          | 0.6302   |
| 0.3146        | 13.0  | 2132 | 0.9592          | 0.6616   |
| 0.3172        | 14.0  | 2296 | 0.9733          | 0.6475   |
| 0.3091        | 15.0  | 2460 | 0.9679          | 0.6540   |
| 0.3071        | 16.0  | 2624 | 0.9691          | 0.6508   |
| 0.3073        | 17.0  | 2788 | 0.9566          | 0.6616   |
| 0.2953        | 18.0  | 2952 | 0.9579          | 0.6486   |
| 0.3014        | 19.0  | 3116 | 0.9578          | 0.6605   |
| 0.2909        | 20.0  | 3280 | 0.9599          | 0.6551   |


### Framework versions

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