README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - AI-Lab-Makerere/beans
metrics:
  - accuracy
base_model: microsoft/beit-base-patch16-384
model-index:
  - name: beit_large512_fine_tuned
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: beans
          type: beans
          config: train
          split: validation
          args: train
        metrics:
          - type: accuracy
            value: 0.9924812030075187
            name: Accuracy

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