THIS IS A TEST REPO FOR DEBUGGING!
This repo is here as a result of playing with and debugging training scripts and push to hub features. As such, the TesnorFlow and PyTorch models will be out of sync and different weights may be push at any time, including pushing models with very low performance.
vit-base-beans
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset. It achieves the following results on the evaluation set:
- Loss: 0.0630
- Accuracy: 0.9850
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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.3038 | 1.0 | 130 | 0.2396 | 0.9624 |
0.1609 | 2.0 | 260 | 0.1130 | 0.9774 |
0.2313 | 3.0 | 390 | 0.0809 | 0.9850 |
0.1436 | 4.0 | 520 | 0.0738 | 0.9850 |
0.1086 | 5.0 | 650 | 0.0630 | 0.9850 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.14.0.dev20221118
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
- Downloads last month
- 15
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for amyeroberts/vit-base-beans
Base model
google/vit-base-patch16-224-in21k