Impact of Weight Decay on MBart-large-50 for EN-ES
Collection
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Updated
This model is a fine-tuned version of facebook/mbart-large-50 on the None 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 | Bleu | Rouge |
---|---|---|---|---|---|
1.4571 | 1.0 | 4500 | 1.0262 | 41.9188 | {'rouge1': 0.6701489298042851, 'rouge2': 0.4850120961190509, 'rougeL': 0.6479081216501843, 'rougeLsum': 0.6480345623292922} |
0.889 | 2.0 | 9000 | 0.9559 | 44.3378 | {'rouge1': 0.6920481616267358, 'rouge2': 0.5087283264258592, 'rougeL': 0.6709294966142768, 'rougeLsum': 0.6710449317682404} |
0.7134 | 3.0 | 13500 | 0.9416 | 44.9705 | {'rouge1': 0.7026762914671131, 'rouge2': 0.5192700210995049, 'rougeL': 0.6817974408692513, 'rougeLsum': 0.6819680202609157} |
0.6098 | 4.0 | 18000 | 0.9547 | 45.1741 | {'rouge1': 0.7051668954804624, 'rouge2': 0.5222186626492409, 'rougeL': 0.6844002112351866, 'rougeLsum': 0.6845851183829141} |
Base model
facebook/mbart-large-50