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 |
---|---|---|---|---|---|
1.4485 | 1.0 | 4500 | 1.0236 | 42.1586 | {'rouge1': 0.6728104679322686, 'rouge2': 0.4866267759088613, 'rougeL': 0.6507619922873461, 'rougeLsum': 0.6508024989844624} |
0.8867 | 2.0 | 9000 | 0.9542 | 44.1945 | {'rouge1': 0.6933374960151913, 'rouge2': 0.5090654274262618, 'rougeL': 0.6722360570050694, 'rougeLsum': 0.6723972406375381} |
0.7112 | 3.0 | 13500 | 0.9408 | 44.9173 | {'rouge1': 0.7047659807760827, 'rouge2': 0.5200169348076622, 'rougeL': 0.6839031690668775, 'rougeLsum': 0.6842067045539153} |
0.6075 | 4.0 | 18000 | 0.9532 | 45.2020 | {'rouge1': 0.7070170730434684, 'rouge2': 0.5239391023023636, 'rougeL': 0.6863309446860562, 'rougeLsum': 0.6866635686411662} |
Base model
facebook/mbart-large-50