End of training

README.md

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+---
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: facebook/mbart-large-50-many-to-many-mmt
+metrics:
+- bleu
+- rouge
+model-index:
+- name: mbart-large-50-many-to-many-mmt-ICFOSS-Malayalam_English_Translation
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# 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](https://huggingface.co/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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