---
library_name: transformers
license: apache-2.0
base_model: c14kevincardenas/ClimBEiTv2
tags:
- knowledge_distillation
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilevit-x-small_alpha0.7_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-x-small_alpha0.7_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: 0.8319
- Accuracy: 0.6650

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1391        | 1.0   | 90   | 1.3902          | 0.2895   |
| 1.0994        | 2.0   | 180  | 1.3219          | 0.3765   |
| 0.9868        | 3.0   | 270  | 1.1753          | 0.4664   |
| 0.8583        | 4.0   | 360  | 1.0554          | 0.5277   |
| 0.752         | 5.0   | 450  | 0.9602          | 0.5840   |
| 0.7175        | 6.0   | 540  | 0.9255          | 0.5761   |
| 0.6641        | 7.0   | 630  | 0.8845          | 0.6324   |
| 0.6509        | 8.0   | 720  | 0.9110          | 0.6028   |
| 0.6031        | 9.0   | 810  | 0.8721          | 0.6374   |
| 0.6017        | 10.0  | 900  | 0.8564          | 0.6522   |
| 0.5642        | 11.0  | 990  | 0.8444          | 0.6482   |
| 0.5584        | 12.0  | 1080 | 0.8647          | 0.6364   |
| 0.5325        | 13.0  | 1170 | 0.8772          | 0.6294   |
| 0.5035        | 14.0  | 1260 | 0.8566          | 0.6354   |
| 0.5084        | 15.0  | 1350 | 0.8670          | 0.6383   |
| 0.4972        | 16.0  | 1440 | 0.8465          | 0.6551   |
| 0.4891        | 17.0  | 1530 | 0.8490          | 0.6443   |
| 0.4841        | 18.0  | 1620 | 0.8504          | 0.6551   |
| 0.4713        | 19.0  | 1710 | 0.8319          | 0.6650   |
| 0.4845        | 20.0  | 1800 | 0.8481          | 0.6542   |


### Framework versions

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