EC-Seq2Seq
Collection
12 items
•
Updated
This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
---|---|---|---|---|---|---|
1.0322 | 1.0 | 663 | 0.7891 | 0.639 | 0.4989 | 0.5491 |
0.8545 | 2.0 | 1326 | 0.7433 | 0.6461 | 0.5057 | 0.5556 |
0.758 | 3.0 | 1989 | 0.7299 | 0.647 | 0.5033 | 0.5547 |
0.6431 | 4.0 | 2652 | 0.7185 | 0.6556 | 0.5101 | 0.5616 |
0.6058 | 5.0 | 3315 | 0.7126 | 0.6537 | 0.5144 | 0.5638 |
0.5726 | 6.0 | 3978 | 0.7117 | 0.6567 | 0.5169 | 0.5666 |
0.5168 | 7.0 | 4641 | 0.7150 | 0.6585 | 0.5154 | 0.566 |
0.5011 | 8.0 | 5304 | 0.7220 | 0.6568 | 0.5164 | 0.5664 |
0.4803 | 9.0 | 5967 | 0.7208 | 0.6573 | 0.5161 | 0.5662 |
0.4577 | 10.0 | 6630 | 0.7223 | 0.6572 | 0.5164 | 0.5662 |