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ViT-GPT2

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metadata
library_name: transformers
base_model: motheecreator/ViT-GPT2-Image_Captioning_model
tags:
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: ViT-GPT2
    results: []

ViT-GPT2

This model is a fine-tuned version of motheecreator/ViT-GPT2-Image_Captioning_model on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1879
  • Rouge2 Precision: None
  • Rouge2 Recall: None
  • Rouge2 Fmeasure: 0.1506
  • Bleu: 9.3133

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: 8
  • total_train_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge2 Precision Rouge2 Recall Rouge2 Fmeasure Bleu
2.2959 0.9993 1171 2.2239 None None 0.1474 8.9628
2.1491 1.9985 2342 2.1879 None None 0.1506 9.3133

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0
  • Datasets 3.0.0
  • Tokenizers 0.19.1