---
license: apache-2.0
base_model: microsoft/beit-large-patch16-384
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beit-large-patch16-384-limb-person-crop-8_5e-5_5e-3_0.1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# beit-large-patch16-384-limb-person-crop-8_5e-5_5e-3_0.1

This model is a fine-tuned version of [microsoft/beit-large-patch16-384](https://huggingface.co/microsoft/beit-large-patch16-384) on the c14kevincardenas/beta_caller_284_person_crop dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8117
- Accuracy: 0.7521

## 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: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3279        | 1.0   | 214  | 1.5112          | 0.3665   |
| 1.1631        | 2.0   | 428  | 1.0103          | 0.6476   |
| 1.1391        | 3.0   | 642  | 0.9429          | 0.6625   |
| 1.0529        | 4.0   | 856  | 0.9844          | 0.6360   |
| 1.0353        | 5.0   | 1070 | 0.9350          | 0.6758   |
| 0.9736        | 6.0   | 1284 | 0.8371          | 0.7421   |
| 0.9167        | 7.0   | 1498 | 0.8476          | 0.7463   |
| 0.8947        | 8.0   | 1712 | 0.8117          | 0.7521   |
| 0.8162        | 9.0   | 1926 | 0.8268          | 0.7587   |
| 0.7906        | 10.0  | 2140 | 0.8129          | 0.7670   |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1