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clip-vit-bert-coco – AI Model by christti | AlphaNeural AI
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clip-vit-bert-coco
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transformers
safetensors
vision-text-dual-encoder
feature-extraction
generated_from_trainer
ydshieh/coco_dataset_script
endpoints_compatible
us
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clip-vit-bert-coco
This model was trained from scratch on the ydshieh/coco_dataset_script 2017 dataset. It achieves the following results on the evaluation set:
eval_loss: 4.1888
eval_runtime: 5.7658
eval_samples_per_second: 22.2
eval_steps_per_second: 0.173
step: 0
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: 128
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0
mixed_precision_training: Native AMP
Framework versions
Transformers 4.39.0.dev0
Pytorch 2.2.1
Datasets 2.18.0
Tokenizers 0.15.2
