clip-vit-base-patch16-finetuned-openai-clip-vit-base-patch16-emnist-letter – AI Model by tangg555 | AlphaNeural AI

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tangg555/
clip-vit-base-patch16-finetuned-openai-clip-vit-base-patch16-emnist-letter

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image-classification

generated_from_trainer

openai/clip-vit-base-patch16

autotrain_compatible

endpoints_compatible

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clip-vit-base-patch16-finetuned-openai-clip-vit-base-patch16-emnist-letter

This model is a fine-tuned version of openai/clip-vit-base-patch16 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1460
Accuracy: 0.9468

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0535	0.9994	877	0.3616	0.8803
0.9258	2.0	1755	0.2692	0.9015
0.7331	2.9994	2632	0.2283	0.9207
0.7137	4.0	3510	0.1815	0.9353
0.6585	4.9994	4387	0.1889	0.9324
0.6366	6.0	5265	0.1688	0.9376
0.6284	6.9994	6142	0.1565	0.9424
0.5834	8.0	7020	0.1541	0.9433
0.5159	8.9994	7897	0.1425	0.9485
0.5233	9.9943	8770	0.1460	0.9468

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1