Hugging Face's logo

NourFakih
/
Vit-GPT2-COCO2017Flickr-85k-11

Image-Text-to-Text
Transformers
TensorBoard
Safetensors
vision-encoder-decoder
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
Edit model card

Vit-GPT2-COCO2017Flickr-85k-11

This model is a fine-tuned version of NourFakih/Vit-GPT2-COCO2017Flickr-85k-11 on an unknown dataset. It achieves the following results on the evaluation set:

  • Gen Len: 12.1495
  • Loss: 0.5306
  • Rouge1: 40.0349
  • Rouge2: 14.6303
  • Rougel: 36.2382
  • Rougelsum: 36.2213

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Gen Len Validation Loss Rouge1 Rouge2 Rougel Rougelsum
0.378 0.0933 500 11.7725 0.4693 40.2274 15.0119 36.4563 36.4656
0.3748 0.1866 1000 12.1668 0.4640 40.199 15.321 36.4279 36.4457
0.374 0.2799 1500 11.8 0.4669 39.9523 15.0587 36.3639 36.375
0.3721 0.3732 2000 11.2095 0.4645 40.3597 15.2173 36.6938 36.705
0.3673 0.4665 2500 11.9343 0.4632 40.3875 15.2532 36.5923 36.6182
0.365 0.5599 3000 12.2647 0.4623 39.9395 15.0315 36.1682 36.1781
0.3652 0.6532 3500 11.8965 0.4611 39.8792 14.9961 36.2488 36.2734
0.3601 0.7465 4000 12.0545 0.4625 40.57 15.2972 36.8012 36.8227
0.3574 0.8398 4500 11.7287 0.4608 40.3276 15.1742 36.7679 36.7575
0.351 0.9331 5000 11.7662 0.4650 40.7345 15.5295 37.0769 37.0911
0.3322 1.0264 5500 12.06 0.4831 40.5582 15.2954 36.6682 36.6694
0.2914 1.1197 6000 11.8405 0.4902 40.054 15.019 36.5476 36.556
0.2945 1.2130 6500 11.8422 0.4863 40.3126 15.3154 36.61 36.6146
0.2845 1.3063 7000 12.0445 0.4883 40.228 15.0904 36.3179 36.3086
0.2879 1.3996 7500 11.9358 0.4833 40.6501 15.5682 36.8945 36.8823
0.2859 1.4930 8000 12.1743 0.4833 40.3187 15.0418 36.3561 36.3582
0.2844 1.5863 8500 12.1702 0.4884 40.2896 15.1032 36.4039 36.3862
0.2838 1.6796 9000 11.9588 0.4902 40.3419 15.1863 36.4631 36.4728
0.2789 1.7729 9500 12.0567 0.4865 40.6284 15.3404 36.7035 36.6876
0.2758 1.8662 10000 11.823 0.4909 40.1138 14.9247 36.4884 36.4836
0.2741 1.9595 10500 11.9537 0.4892 40.3204 14.9594 36.539 36.5311
0.253 2.0529 11000 11.9712 0.5201 40.0224 14.9662 36.3433 36.3705
0.2261 2.1462 11500 11.8918 0.5248 39.698 14.3092 35.9144 35.9107
0.2245 2.2395 12000 12.0252 0.5204 40.136 14.8487 36.4154 36.3989
0.2293 2.3328 12500 11.8622 0.5261 39.9269 14.6665 36.2594 36.2517
0.2255 2.4261 13000 11.9165 0.5217 40.1403 14.7327 36.4161 36.4139
0.228 2.5195 13500 11.9477 0.5267 39.7979 14.4362 36.0457 36.0611
0.2233 2.6128 14000 12.0495 0.5299 39.8343 14.4579 36.0728 36.0824
0.2239 2.7062 14500 12.1308 0.5274 39.9561 14.5286 36.1101 36.1017
0.2254 2.7995 15000 12.0845 0.5292 39.9252 14.5215 36.1396 36.1203
0.2182 2.8928 15500 12.115 0.5297 39.9487 14.5406 36.1582 36.1321
0.221 2.9861 16000 12.1495 0.5306 40.0349 14.6303 36.2382 36.2213

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1
Downloads last month
17
Safetensors
Model size
239M params
Tensor type
F32
·
Inference API
Image-Text-to-Text
Inference API (serverless) does not yet support transformers models for this pipeline type.

Model tree for NourFakih/Vit-GPT2-COCO2017Flickr-85k-11

Unable to build the model tree, the base model loops to the model itself. Learn more.

Space using NourFakih/Vit-GPT2-COCO2017Flickr-85k-11 1

Evaluation results

Metadata error: specify a dataset to view leaderboard