---
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-t2-4heads-1layers-5e-4lr
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# finetuned-beit-limb-seq-t2-4heads-1layers-5e-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_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3965
- Accuracy: 0.9180

## 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: 0.0005
- 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: 15.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5406        | 1.0   | 180  | 0.4804          | 0.8883   |
| 0.4852        | 2.0   | 360  | 0.5457          | 0.8794   |
| 0.4664        | 3.0   | 540  | 0.4203          | 0.9051   |
| 0.4929        | 4.0   | 720  | 0.4349          | 0.9002   |
| 0.4334        | 5.0   | 900  | 0.4816          | 0.8765   |
| 0.4709        | 6.0   | 1080 | 0.4574          | 0.8933   |
| 0.4525        | 7.0   | 1260 | 0.4652          | 0.8883   |
| 0.4601        | 8.0   | 1440 | 0.4387          | 0.9002   |
| 0.4361        | 9.0   | 1620 | 0.4138          | 0.9071   |
| 0.4297        | 10.0  | 1800 | 0.4089          | 0.9140   |
| 0.4           | 11.0  | 1980 | 0.4000          | 0.9200   |
| 0.4035        | 12.0  | 2160 | 0.4260          | 0.9071   |
| 0.3875        | 13.0  | 2340 | 0.4088          | 0.9101   |
| 0.4117        | 14.0  | 2520 | 0.3965          | 0.9180   |
| 0.3518        | 15.0  | 2700 | 0.3987          | 0.9160   |


### Framework versions

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