---
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-5lr
  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-5lr

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: 0.3956
- Accuracy: 0.9121

## 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: 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: 10.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7468        | 1.0   | 180  | 0.6694          | 0.8221   |
| 0.4348        | 2.0   | 360  | 0.4541          | 0.9051   |
| 0.4143        | 3.0   | 540  | 0.4037          | 0.9130   |
| 0.4151        | 4.0   | 720  | 0.4072          | 0.9061   |
| 0.3883        | 5.0   | 900  | 0.4024          | 0.9209   |
| 0.4177        | 6.0   | 1080 | 0.4007          | 0.9121   |
| 0.3858        | 7.0   | 1260 | 0.3984          | 0.9140   |
| 0.4052        | 8.0   | 1440 | 0.4064          | 0.9150   |
| 0.3904        | 9.0   | 1620 | 0.3963          | 0.9160   |
| 0.3725        | 10.0  | 1800 | 0.3956          | 0.9121   |


### Framework versions

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