---
library_name: transformers
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: jaffe_V2_50
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8
---

<!-- 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. -->

# jaffe_V2_50

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7217
- Accuracy: 0.8

## 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: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 1.9638          | 0.2333   |
| No log        | 2.0   | 2    | 1.7893          | 0.3333   |
| No log        | 3.0   | 3    | 1.8759          | 0.1667   |
| No log        | 4.0   | 4    | 1.6759          | 0.3667   |
| No log        | 5.0   | 5    | 1.5139          | 0.5      |
| No log        | 6.0   | 6    | 1.4280          | 0.5667   |
| No log        | 7.0   | 7    | 1.3688          | 0.5667   |
| No log        | 8.0   | 8    | 1.2819          | 0.6      |
| No log        | 9.0   | 9    | 1.1884          | 0.6      |
| 1.5329        | 10.0  | 10   | 1.1448          | 0.6      |
| 1.5329        | 11.0  | 11   | 1.0732          | 0.7      |
| 1.5329        | 12.0  | 12   | 0.9793          | 0.7333   |
| 1.5329        | 13.0  | 13   | 0.8830          | 0.7333   |
| 1.5329        | 14.0  | 14   | 0.8366          | 0.7667   |
| 1.5329        | 15.0  | 15   | 0.8027          | 0.7333   |
| 1.5329        | 16.0  | 16   | 0.7952          | 0.7333   |
| 1.5329        | 17.0  | 17   | 0.7746          | 0.7333   |
| 1.5329        | 18.0  | 18   | 0.7571          | 0.7667   |
| 1.5329        | 19.0  | 19   | 0.7256          | 0.7667   |
| 0.5232        | 20.0  | 20   | 0.7217          | 0.8      |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0