Swin_BART_KTVIC

Skyler215/Swin_BART_KTVIC

Swin_BART_KTVIC is a image-text-to-text model from Skyler215. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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Model card

From the Hugging Face model README

Swin_BART_KTVIC

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

Loss: 1.1684
Bleu-4: 0.2074

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: 2
total_train_batch_size: 64
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
lr_scheduler_warmup_steps: 300
num_epochs: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu-4
No log	1.0	236	1.4136	0.1220
1.9745	2.0	472	1.2818	0.1443
1.3205	3.0	708	1.2124	0.1686
1.1231	4.0	944	1.1763	0.1860
1.1231	5.0	1180	1.1625	0.1949
0.9658	6.0	1416	1.1590	0.2025
0.8276	7.0	1652	1.1684	0.2074

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
Created: Nov 28, 2024
Updated: Nov 29, 2024