clip-DIT-finetuned – AI Model by sharkMeow | AlphaNeural AI

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sharkMeow/
clip-DIT-finetuned

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vision-text-dual-encoder

feature-extraction

generated_from_trainer

ckiplab/bert-base-chinese

endpoints_compatible

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clip-DIT-finetuned

This model is a fine-tuned version of ckiplab/bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7439

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: 1e-05
train_batch_size: 64
eval_batch_size: 100
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 100.0

Training results

Training Loss	Epoch	Step	Validation Loss
2.648	10.0	780	2.4340
0.797	20.0	1560	1.5686
0.3112	30.0	2340	1.2473
0.1758	40.0	3120	1.0606
0.1176	50.0	3900	0.9469
0.09	60.0	4680	0.8606
0.0733	70.0	5460	0.8265
0.0631	80.0	6240	0.7704
0.0576	90.0	7020	0.7507
0.0545	100.0	7800	0.7439

Framework versions

Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1