---
library_name: transformers
license: apache-2.0
base_model: c14kevincardenas/beit-large-patch16-384-limb-person-crop
tags:
- image-sequence-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-beit-limb-seq-t4-8heads-2layers-1e-4lr
  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. -->

# finetuned-beit-limb-seq-t4-8heads-2layers-1e-4lr

This model is a fine-tuned version of [c14kevincardenas/beit-large-patch16-384-limb-person-crop](https://huggingface.co/c14kevincardenas/beit-large-patch16-384-limb-person-crop) on the c14kevincardenas/beta_caller_284_person_crop_seq_withlimb_4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3936
- Accuracy: 0.9186

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2014
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 20.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7398        | 1.0   | 148  | 0.5190          | 0.8778   |
| 0.4307        | 2.0   | 296  | 0.4325          | 0.9006   |
| 0.5113        | 3.0   | 444  | 0.4381          | 0.9102   |
| 0.4097        | 4.0   | 592  | 0.4231          | 0.9006   |
| 0.4298        | 5.0   | 740  | 0.3942          | 0.9198   |
| 0.4204        | 6.0   | 888  | 0.4213          | 0.9042   |
| 0.4149        | 7.0   | 1036 | 0.4032          | 0.9102   |
| 0.4028        | 8.0   | 1184 | 0.3973          | 0.9162   |
| 0.4611        | 9.0   | 1332 | 0.3936          | 0.9186   |
| 0.3807        | 10.0  | 1480 | 0.3946          | 0.9186   |
| 0.3918        | 11.0  | 1628 | 0.3983          | 0.9198   |
| 0.3929        | 12.0  | 1776 | 0.4013          | 0.9150   |
| 0.368         | 13.0  | 1924 | 0.4185          | 0.9090   |
| 0.3921        | 14.0  | 2072 | 0.4193          | 0.9102   |
| 0.3706        | 15.0  | 2220 | 0.4134          | 0.9138   |
| 0.3639        | 16.0  | 2368 | 0.3938          | 0.9198   |
| 0.3335        | 17.0  | 2516 | 0.4057          | 0.9138   |
| 0.374         | 18.0  | 2664 | 0.4089          | 0.9174   |
| 0.3723        | 19.0  | 2812 | 0.3999          | 0.9174   |
| 0.3055        | 20.0  | 2960 | 0.4020          | 0.9174   |


### Framework versions

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