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End of training
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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: t5-small-t5-dialogue-summarizer
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: validation
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 43.3371

t5-small-t5-dialogue-summarizer

This model is a fine-tuned version of t5-small on the samsum dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7032
  • Rouge1: 43.3371
  • Rouge2: 20.6294
  • Rougel: 36.6607
  • Rougelsum: 40.209
  • Gen Len: 16.698

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 460 1.8115 41.2589 18.3552 34.5107 38.2488 16.8068
1.9846 2.0 921 1.7892 41.1617 18.4345 34.745 38.2061 16.6247
1.9568 3.0 1381 1.7757 41.7317 19.0104 35.2965 38.6958 16.4059
1.9298 4.0 1842 1.7573 42.0478 19.1229 35.4855 39.0882 16.6235
1.9049 5.0 2302 1.7496 42.4985 19.5594 35.9228 39.4201 16.5416
1.8852 6.0 2763 1.7411 42.3214 19.6152 35.7488 39.3079 16.7139
1.8674 7.0 3223 1.7335 42.3206 19.7528 35.9918 39.2783 16.5073
1.855 8.0 3684 1.7300 42.9099 20.2273 36.4393 39.8506 16.61
1.8435 9.0 4144 1.7225 42.9661 20.3074 36.3468 39.8945 16.7103
1.8342 10.0 4605 1.7198 43.0181 20.2982 36.4202 39.9022 16.7726
1.8216 11.0 5065 1.7169 43.0296 20.5422 36.6314 40.111 16.6883
1.8168 12.0 5526 1.7144 43.3035 20.7167 36.7924 40.2953 16.7787
1.8168 13.0 5986 1.7104 43.2258 20.7416 36.7823 40.2551 16.7286
1.8088 14.0 6447 1.7075 43.3982 20.8281 36.8254 40.3198 16.7384
1.8008 15.0 6907 1.7079 43.3077 20.7164 36.6791 40.2372 16.687
1.8014 16.0 7368 1.7047 43.1989 20.6984 36.7104 40.2285 16.6479
1.7934 17.0 7828 1.7034 43.4149 20.7879 36.7308 40.3556 16.7922
1.7894 18.0 8289 1.7041 43.2962 20.7667 36.7017 40.28 16.6883
1.7914 19.0 8749 1.7037 43.2489 20.6943 36.676 40.1802 16.6932
1.7827 19.98 9200 1.7032 43.3371 20.6294 36.6607 40.209 16.698

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0