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flan-t5-rouge-squad-qg

Text2Text Generation
Transformers
Safetensors
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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flan-t5-rouge-squad-qg / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-base
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: flan-t5-rouge-squad-qg
    results: []

flan-t5-rouge-squad-qg

This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3225
  • Rouge1: 0.4603
  • Rouge2: 0.1838
  • Rougel: 0.4115
  • Rougelsum: 0.4478

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: 0.0003
  • train_batch_size: 24
  • eval_batch_size: 24
  • seed: 42
  • 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: 30

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
16.5081 1.0 3 15.3312 0.2528 0.1156 0.2032 0.2053
8.4005 2.0 6 4.6577 0.2538 0.1115 0.1987 0.2066
4.0936 3.0 9 4.0634 0.2540 0.1245 0.2186 0.2184
3.6521 4.0 12 3.6769 0.2898 0.1640 0.2539 0.2607
3.1589 5.0 15 3.1339 0.3017 0.1714 0.2645 0.2717
2.5217 6.0 18 2.3186 0.3017 0.1714 0.2645 0.2717
1.5472 7.0 21 0.9929 0.3164 0.1571 0.2498 0.2563
1.5284 8.0 24 0.6101 0.2596 0.1178 0.2018 0.2043
1.2359 9.0 27 0.4815 0.2596 0.1178 0.2018 0.2043
1.1669 10.0 30 0.3870 0.5138 0.2379 0.4589 0.4960
0.6514 11.0 33 0.3166 0.5138 0.2379 0.4589 0.4960
0.3465 12.0 36 0.2860 0.5138 0.2379 0.4589 0.4960
0.2721 13.0 39 0.2776 0.5138 0.2379 0.4589 0.4960
0.4964 14.0 42 0.2746 0.5152 0.2444 0.4655 0.4940
0.2382 15.0 45 0.2761 0.4675 0.1901 0.4208 0.4483
0.5074 16.0 48 0.2801 0.4675 0.1901 0.4208 0.4483
0.353 17.0 51 0.2858 0.4675 0.1901 0.4208 0.4483
0.1808 18.0 54 0.2916 0.4675 0.1901 0.4208 0.4483
0.2506 19.0 57 0.2961 0.4665 0.1838 0.4145 0.4506
0.2296 20.0 60 0.3027 0.5138 0.2379 0.4589 0.4960
0.3785 21.0 63 0.3073 0.5138 0.2379 0.4589 0.4960
0.2014 22.0 66 0.3107 0.5138 0.2379 0.4589 0.4960
0.4355 23.0 69 0.3131 0.5138 0.2379 0.4589 0.4960
0.1727 24.0 72 0.3159 0.5138 0.2379 0.4589 0.4960
0.1342 25.0 75 0.3173 0.5138 0.2379 0.4589 0.4960
0.193 26.0 78 0.3200 0.5138 0.2379 0.4589 0.4960
0.1703 27.0 81 0.3211 0.5138 0.2379 0.4589 0.4960
0.0676 28.0 84 0.3216 0.4603 0.1838 0.4115 0.4478
0.1207 29.0 87 0.3222 0.4603 0.1838 0.4115 0.4478
0.1002 30.0 90 0.3225 0.4603 0.1838 0.4115 0.4478

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.21.0