---
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_alpha0.5_temp3.0
  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_alpha0.5_temp3.0

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: 0.8337
- Accuracy: 0.6789

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2251        | 1.0   | 90   | 1.4083          | 0.2441   |
| 1.1754        | 2.0   | 180  | 1.3374          | 0.3063   |
| 1.086         | 3.0   | 270  | 1.2295          | 0.3844   |
| 0.9164        | 4.0   | 360  | 1.0471          | 0.5208   |
| 0.8124        | 5.0   | 450  | 0.9794          | 0.5692   |
| 0.757         | 6.0   | 540  | 0.9078          | 0.6136   |
| 0.7021        | 7.0   | 630  | 0.8754          | 0.6423   |
| 0.6535        | 8.0   | 720  | 0.8976          | 0.6206   |
| 0.5973        | 9.0   | 810  | 0.8455          | 0.6719   |
| 0.5778        | 10.0  | 900  | 0.8477          | 0.6532   |
| 0.5556        | 11.0  | 990  | 0.8395          | 0.6660   |
| 0.5226        | 12.0  | 1080 | 0.8487          | 0.6542   |
| 0.4926        | 13.0  | 1170 | 0.8610          | 0.6482   |
| 0.4766        | 14.0  | 1260 | 0.8337          | 0.6789   |
| 0.4763        | 15.0  | 1350 | 0.8482          | 0.6650   |
| 0.45          | 16.0  | 1440 | 0.8374          | 0.6700   |
| 0.4468        | 17.0  | 1530 | 0.8378          | 0.6759   |
| 0.4267        | 18.0  | 1620 | 0.8382          | 0.6729   |
| 0.4321        | 19.0  | 1710 | 0.8399          | 0.6719   |
| 0.4318        | 20.0  | 1800 | 0.8438          | 0.6729   |


### Framework versions

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