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flan-t5-base-finetuned-FOMC

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

flan-t5-base-finetuned-FOMC

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: 2.2508
  • Rouge1: 33.4635
  • Rouge2: 20.2223
  • Rougel: 30.0686
  • Rougelsum: 30.5667
  • Gen Len: 19.0

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 10 2.6211 30.3857 18.7991 27.6215 28.1883 19.0
No log 2.0 20 2.5670 30.484 18.1632 27.4386 28.171 19.0
No log 3.0 30 2.5087 29.9232 17.615 26.8812 27.6851 19.0
No log 4.0 40 2.4691 29.9232 17.615 26.8812 27.6851 19.0
No log 5.0 50 2.4427 30.3286 17.7647 27.3411 28.085 19.0
No log 6.0 60 2.4165 30.7106 18.153 27.7262 28.3967 19.0
No log 7.0 70 2.3916 31.0342 18.6915 28.0288 28.757 19.0
No log 8.0 80 2.3753 31.0342 18.6915 28.0288 28.757 19.0
No log 9.0 90 2.3556 31.0342 18.6915 28.0288 28.757 19.0
No log 10.0 100 2.3410 32.0795 19.3562 29.0882 29.5601 19.0
No log 11.0 110 2.3272 32.0795 19.3562 29.0882 29.5601 19.0
No log 12.0 120 2.3180 32.5188 19.5364 29.4727 29.6928 19.0
No log 13.0 130 2.3097 32.5188 19.5364 29.4727 29.4824 19.0
No log 14.0 140 2.3008 32.5188 19.5364 29.4727 29.4824 19.0
No log 15.0 150 2.2947 32.5188 19.5364 29.4727 29.4824 19.0
No log 16.0 160 2.2861 32.5188 19.5364 29.4727 29.4824 19.0
No log 17.0 170 2.2791 33.4635 20.2223 30.0686 30.5667 19.0
No log 18.0 180 2.2755 33.4635 20.2223 30.0686 30.5667 19.0
No log 19.0 190 2.2712 33.4635 20.2223 30.0686 30.5667 19.0
No log 20.0 200 2.2661 33.4635 20.2223 30.0686 30.5667 19.0
No log 21.0 210 2.2623 33.4635 20.2223 30.0686 30.5667 19.0
No log 22.0 220 2.2602 33.4635 20.2223 30.0686 30.5667 19.0
No log 23.0 230 2.2588 33.4635 20.2223 30.0686 30.5667 19.0
No log 24.0 240 2.2561 33.4635 20.2223 30.0686 30.5667 19.0
No log 25.0 250 2.2545 33.4635 20.2223 30.0686 30.5667 19.0
No log 26.0 260 2.2532 33.4635 20.2223 30.0686 30.5667 19.0
No log 27.0 270 2.2526 33.4635 20.2223 30.0686 30.5667 19.0
No log 28.0 280 2.2518 33.4635 20.2223 30.0686 30.5667 19.0
No log 29.0 290 2.2509 33.4635 20.2223 30.0686 30.5667 19.0
No log 30.0 300 2.2508 33.4635 20.2223 30.0686 30.5667 19.0

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3