End of training

README.md

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+---
+license: cc-by-nc-4.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: facebook/nllb-200-1.3B
+metrics:
+- bleu
+- rouge
+model-index:
+- name: nllb-200-1.3B-ICFOSS_Malayalam_Tamil_Translator
+  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. -->
+
+# nllb-200-1.3B-ICFOSS_Malayalam_Tamil_Translator
+
+This model is a fine-tuned version of [facebook/nllb-200-1.3B](https://huggingface.co/facebook/nllb-200-1.3B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8336
+- Bleu: 30.1755
+- Rouge: {'rouge1': 0.27813852813852813, 'rouge2': 0.14151205936920222, 'rougeL': 0.268193413729128, 'rougeLsum': 0.2691068851783137}
+- Chrf: {'score': 66.57581227024936, '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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Rouge                                                                                                                         | Chrf                                                                      |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-----------------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------:|
+| 0.9998        | 1.0   | 3806  | 0.8684          | 28.6085 | {'rouge1': 0.2776283240568955, 'rouge2': 0.14373067408781692, 'rougeL': 0.26886982065553494, 'rougeLsum': 0.2699984539270253} | {'score': 65.8388692774937, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
+| 0.8913        | 2.0   | 7612  | 0.8432          | 29.6027 | {'rouge1': 0.27813852813852813, 'rouge2': 0.14151205936920222, 'rougeL': 0.268193413729128, 'rougeLsum': 0.2691068851783137}  | {'score': 66.3019387532507, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
+| 0.8506        | 3.0   | 11418 | 0.8330          | 29.8285 | {'rouge1': 0.27813852813852813, 'rouge2': 0.14151205936920222, 'rougeL': 0.268193413729128, 'rougeLsum': 0.2691068851783137}  | {'score': 66.55262372617446, 'char_order': 6, 'word_order': 0, 'beta': 2} |
+| 0.8356        | 4.0   | 15224 | 0.8336          | 30.1355 | {'rouge1': 0.27813852813852813, 'rouge2': 0.14336734693877548, 'rougeL': 0.2690772521129664, 'rougeLsum': 0.2704442383013811} | {'score': 66.59248639173376, 'char_order': 6, 'word_order': 0, 'beta': 2} |
+| 0.8321        | 5.0   | 19030 | 0.8336          | 30.1755 | {'rouge1': 0.27813852813852813, 'rouge2': 0.14151205936920222, 'rougeL': 0.268193413729128, 'rougeLsum': 0.2691068851783137}  | {'score': 66.57581227024936, 'char_order': 6, 'word_order': 0, 'beta': 2} |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.40.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

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