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Vit-GPT2-UCA-UCF-05 – AI Model by Image-Captioning-ML | AlphaNeural AI
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Image-Captioning-ML
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Vit-GPT2-UCA-UCF-05
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transformers
tensorboard
safetensors
vision-encoder-decoder
image-text-to-text
generated_from_trainer
Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-85k-09
finetune
apache-2.0
endpoints_compatible
us
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Vit-GPT2-UCA-UCF-05
This model is a fine-tuned version of
NourFakih/Vit-GPT2-COCO2017Flickr-85k-09
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.2266
eval_rouge1: 28.1525
eval_rouge2: 6.9403
eval_rougeL: 23.8393
eval_rougeLsum: 24.0611
eval_gen_len: 15.274
eval_runtime: 1142.2537
eval_samples_per_second: 8.755
eval_steps_per_second: 2.189
epoch: 0.1770
step: 1000
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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3.0
Framework versions
Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0
