doc-img-classification – AI Model by jnmrr | AlphaNeural AI

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jnmrr/
doc-img-classification

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image-classification

generated_from_trainer

microsoft/dit-base

autotrain_compatible

endpoints_compatible

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doc-img-classification

This model is a fine-tuned version of microsoft/dit-base on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 1.0820
Accuracy: 0.3484
Weighted f1: 0.2183
Micro f1: 0.3484
Macro f1: 0.2173
Weighted recall: 0.3484
Micro recall: 0.3484
Macro recall: 0.3545
Weighted precision: 0.4016
Micro precision: 0.3484
Macro precision: 0.3764

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: 0.001
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Weighted f1	Micro f1	Macro f1	Weighted recall	Micro recall	Macro recall	Weighted precision	Micro precision	Macro precision
1.7064	0.9855	17	1.0820	0.3484	0.2183	0.3484	0.2173	0.3484	0.3484	0.3545	0.4016	0.3484	0.3764

Framework versions

Transformers 4.43.3
Pytorch 2.4.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1