mbart-large-50-many-to-many-mmt-ICFOSS-Malayalam_English_Translation
This model is a fine-tuned version of facebook/mbart-large-50-many-to-many-mmt on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3733
- Bleu: 28.9041
- Rouge: {'rouge1': 0.6211709615166336, 'rouge2': 0.3817538086155071, 'rougeL': 0.5654819931253774, 'rougeLsum': 0.5656455299372645}
- Chrf: {'score': 56.252579884228325, 'char_order': 6, 'word_order': 0, 'beta': 2}
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge | Chrf |
---|---|---|---|---|---|---|
1.5329 | 1.0 | 4700 | 1.4284 | 27.0756 | {'rouge1': 0.6054918604734425, 'rouge2': 0.36327221325964765, 'rougeL': 0.5490261054453232, 'rougeLsum': 0.5491186003413475} | {'score': 54.690919979551, 'char_order': 6, 'word_order': 0, 'beta': 2} |
1.4295 | 2.0 | 9400 | 1.3924 | 28.2063 | {'rouge1': 0.614973366544844, 'rouge2': 0.373550100507563, 'rougeL': 0.5589026806041284, 'rougeLsum': 0.5589661976445393} | {'score': 55.635529686949894, 'char_order': 6, 'word_order': 0, 'beta': 2} |
1.3942 | 3.0 | 14100 | 1.3792 | 28.5831 | {'rouge1': 0.6187502745206666, 'rouge2': 0.37919936984407143, 'rougeL': 0.5626864397042893, 'rougeLsum': 0.5627150169042504} | {'score': 56.019161628219024, 'char_order': 6, 'word_order': 0, 'beta': 2} |
1.3795 | 4.0 | 18800 | 1.3759 | 28.7523 | {'rouge1': 0.620515288235373, 'rouge2': 0.38072092563685545, 'rougeL': 0.5644953116677603, 'rougeLsum': 0.5646285495158272} | {'score': 56.162861197192925, 'char_order': 6, 'word_order': 0, 'beta': 2} |
1.3723 | 5.0 | 23500 | 1.3735 | 28.8675 | {'rouge1': 0.6225302294049915, 'rouge2': 0.382440202243451, 'rougeL': 0.5664785907343486, 'rougeLsum': 0.5666347228887372} | {'score': 56.30835530151895, 'char_order': 6, 'word_order': 0, 'beta': 2} |
1.3684 | 6.0 | 28200 | 1.3731 | 28.8915 | {'rouge1': 0.6214787732761883, 'rouge2': 0.3815472818692578, 'rougeL': 0.5656767538045446, 'rougeLsum': 0.5657190870277087} | {'score': 56.251600472693866, 'char_order': 6, 'word_order': 0, 'beta': 2} |
1.3685 | 7.0 | 32900 | 1.3732 | 28.8953 | {'rouge1': 0.6216361131555139, 'rouge2': 0.3821354228713412, 'rougeL': 0.5655300849639422, 'rougeLsum': 0.565595149126267} | {'score': 56.26874870012928, 'char_order': 6, 'word_order': 0, 'beta': 2} |
1.3678 | 8.0 | 37600 | 1.3733 | 28.9041 | {'rouge1': 0.6211709615166336, 'rouge2': 0.3817538086155071, 'rougeL': 0.5654819931253774, 'rougeLsum': 0.5656455299372645} | {'score': 56.252579884228325, 'char_order': 6, 'word_order': 0, 'beta': 2} |
Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0
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Model tree for ArunIcfoss/mbart-large-50-many-to-many-mmt-ICFOSS-Malayalam_English_Translation
Base model
facebook/mbart-large-50-many-to-many-mmt