---
library_name: transformers
license: apache-2.0
base_model: c14kevincardenas/ClimBEiTv2
tags:
- knowledge_distillation
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilevit-small_alpha0.7_temp5.0
  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

This model is a fine-tuned version of [c14kevincardenas/ClimBEiTv2](https://huggingface.co/c14kevincardenas/ClimBEiTv2) on the c14kevincardenas/beta_caller_284_person_crop_seq_withlimb_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8550
- Accuracy: 0.6680

## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1311        | 1.0   | 90   | 1.4279          | 0.2470   |
| 1.0789        | 2.0   | 180  | 1.3331          | 0.3192   |
| 0.9867        | 3.0   | 270  | 1.2525          | 0.3864   |
| 0.8433        | 4.0   | 360  | 1.0671          | 0.4970   |
| 0.7496        | 5.0   | 450  | 0.9999          | 0.5603   |
| 0.6948        | 6.0   | 540  | 0.9374          | 0.5988   |
| 0.6495        | 7.0   | 630  | 0.9065          | 0.6146   |
| 0.6101        | 8.0   | 720  | 0.9331          | 0.6008   |
| 0.5591        | 9.0   | 810  | 0.8673          | 0.6571   |
| 0.5406        | 10.0  | 900  | 0.8705          | 0.6235   |
| 0.5188        | 11.0  | 990  | 0.8579          | 0.6630   |
| 0.4875        | 12.0  | 1080 | 0.8809          | 0.6324   |
| 0.4596        | 13.0  | 1170 | 0.8904          | 0.6324   |
| 0.4418        | 14.0  | 1260 | 0.8596          | 0.6542   |
| 0.4385        | 15.0  | 1350 | 0.8769          | 0.6304   |
| 0.4175        | 16.0  | 1440 | 0.8625          | 0.6561   |
| 0.413         | 17.0  | 1530 | 0.8578          | 0.6571   |
| 0.3973        | 18.0  | 1620 | 0.8573          | 0.6581   |
| 0.3964        | 19.0  | 1710 | 0.8550          | 0.6680   |
| 0.4004        | 20.0  | 1800 | 0.8711          | 0.6403   |


### Framework versions

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