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IC_ver6N_coco_swin_gpt2_50B_1e

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metadata
base_model: VK246/IC_ver6M_coco_swin_gpt2_50A_1e
tags:
  - generated_from_trainer
datasets:
  - coco
metrics:
  - rouge
model-index:
  - name: IC_ver6N_coco_swin_gpt2_50B_1e
    results: []

IC_ver6N_coco_swin_gpt2_50B_1e

This model is a fine-tuned version of VK246/IC_ver6M_coco_swin_gpt2_50A_1e on the coco dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8687
  • Cider: 72.5295
  • Rouge1: 41.1356
  • Rouge2: 15.6403
  • Rougel: 37.2276
  • Rougelsum: 37.2406
  • Bleu-1: 42.1796
  • Bleu-2: 24.0186
  • Bleu-3: 14.9974
  • Bleu-4: 9.8206
  • Gen Len: 11.3063

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: 96
  • eval_batch_size: 96
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Cider Rouge1 Rouge2 Rougel Rougelsum Bleu-1 Bleu-2 Bleu-3 Bleu-4 Gen Len
0.3812 0.34 1000 1.0009 68.2568 39.9649 14.5975 36.1435 36.1441 41.3234 23.0865 14.2103 9.2075 11.3063
0.5147 0.68 2000 0.8687 72.5295 41.1356 15.6403 37.2276 37.2406 42.1796 24.0186 14.9974 9.8206 11.3063

Framework versions

  • Transformers 4.32.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3