Dit Base Finetuned Rvlcdip Finetuned Data200

🚀 dit-base-finetuned-rvlcdip-finetuned-data200

This model is a fine - tuned version of microsoft/dit-base-finetuned-rvlcdip on the imagefolder dataset. It can be used for image classification tasks and achieves the following results on the evaluation set:

• Loss: 3.0080
• Accuracy: 0.5699

✨ Features

• Based on the pre - trained model [microsoft/dit-base-finetuned-rvlcdip], it is fine - tuned on the imagefolder dataset, which can better adapt to specific image classification tasks.
• The model provides certain accuracy in image classification, with an accuracy rate of 0.5699 on the evaluation set.

📚 Documentation

Model description

This model is a fine - tuned version of [microsoft/dit-base-finetuned-rvlcdip] on the imagefolder dataset.

Intended uses & limitations

The model is mainly intended for image classification tasks. However, more information about its limitations needs to be further explored.

Training and evaluation data

The model is trained and evaluated on the imagefolder dataset. But more detailed information about the data needs to be supplemented.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e - 05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 200

Training results