Edit model card

beit_large512_fine_tuned

This model is a fine-tuned version of microsoft/beit-base-patch16-384 on the beans dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0353
  • Accuracy: 0.9925

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: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • 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: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
4.6571 0.98 16 0.3870 0.8722
0.2299 1.97 32 0.0632 0.9850
0.1435 2.95 48 0.0353 0.9925

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cpu
  • Datasets 2.13.1
  • Tokenizers 0.13.3
Downloads last month
8
Inference Examples
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 Thamer/beit_large512_fine_tuned

Finetuned
(1)
this model

Dataset used to train Thamer/beit_large512_fine_tuned

Evaluation results