---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: recomendation-system
  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. -->

# recomendation-system

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3870
- Accuracy: 0.5658

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.7526        | 1.0   | 612  | 4.7474          | 0.2541   |
| 3.9574        | 2.0   | 1224 | 3.8794          | 0.4050   |
| 3.4665        | 3.0   | 1836 | 3.3852          | 0.4621   |
| 3.0017        | 4.0   | 2448 | 3.0551          | 0.4944   |
| 2.7217        | 5.0   | 3060 | 2.8251          | 0.5137   |
| 2.5752        | 6.0   | 3672 | 2.6569          | 0.5399   |
| 2.5064        | 7.0   | 4284 | 2.5447          | 0.5501   |
| 2.3956        | 8.0   | 4896 | 2.4493          | 0.5631   |
| 2.1768        | 9.0   | 5508 | 2.4040          | 0.5631   |
| 2.2168        | 10.0  | 6120 | 2.3870          | 0.5658   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1