SFT_shadow / README.md
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End of training
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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: shadow
    results: []

shadow

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

  • Loss: 1.2249
  • Rouge1: 0.2638
  • Rouge2: 0.1186
  • Rougel: 0.2171
  • Rougelsum: 0.2169
  • Gen Len: 146.8555

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.6504 1.0 718 1.5109 0.0112 0.0026 0.0098 0.0098 13.3183
1.7193 2.0 1436 1.3836 0.1697 0.0487 0.1355 0.1354 140.8933
1.5492 3.0 2154 1.3174 0.202 0.0564 0.1591 0.1592 153.2811
1.51 4.0 2872 1.2829 0.2152 0.0691 0.1708 0.1709 156.3921
1.4341 5.0 3590 1.2613 0.2336 0.0895 0.1866 0.1866 156.2713
1.4335 6.0 4308 1.2466 0.2534 0.1118 0.2073 0.2075 146.7207
1.4033 7.0 5026 1.2363 0.2591 0.1168 0.213 0.213 144.5354
1.4045 8.0 5744 1.2298 0.261 0.1171 0.2149 0.2149 147.7884
1.3839 9.0 6462 1.2260 0.263 0.1178 0.216 0.2159 147.3518
1.3863 10.0 7180 1.2249 0.2638 0.1186 0.2171 0.2169 146.8555

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0