|
--- |
|
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 |
|
|
