End of training

README.md

@@ -4,6 +4,9 @@ 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_English_Translation1.3b
   results: []
@@ -14,7 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # nllb-200-1.3B-ICFOSS-Malayalam_English_Translation1.3b
 
-This model is a fine-tuned version of [facebook/nllb-200-1.3B](https://huggingface.co/facebook/nllb-200-1.3B) on an unknown dataset.
+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: 1.0536
+- Bleu: 36.7256
+- Rouge: {'rouge1': 0.6977825292445439, 'rouge2': 0.47317224666360513, 'rougeL': 0.6369586014923634, 'rougeLsum': 0.6367120144580565}
+- Chrf: {'score': 63.88643397225133, 'char_order': 6, 'word_order': 0, 'beta': 2}
 
 ## Model description
 
@@ -41,6 +49,19 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: cosine
 - num_epochs: 7
 
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Rouge                                                                                                                        | Chrf                                                                       |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:----------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------:|
+| 1.1683        | 1.0   | 5750  | 1.0774          | 35.9761 | {'rouge1': 0.6937855960659589, 'rouge2': 0.466938063654629, 'rougeL': 0.6325990208208303, 'rougeLsum': 0.6323899971616622}   | {'score': 63.363704282940446, 'char_order': 6, 'word_order': 0, 'beta': 2} |
+| 1.1177        | 2.0   | 11500 | 1.0617          | 36.3486 | {'rouge1': 0.6957984629345982, 'rouge2': 0.47067647725021045, 'rougeL': 0.6351678391451753, 'rougeLsum': 0.6350175761315434} | {'score': 63.657728669261445, 'char_order': 6, 'word_order': 0, 'beta': 2} |
+| 1.102         | 3.0   | 17250 | 1.0559          | 36.7216 | {'rouge1': 0.6970801919668868, 'rouge2': 0.47279660574601357, 'rougeL': 0.6364385448189633, 'rougeLsum': 0.6362592345657716} | {'score': 63.89202343434442, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
+| 1.0967        | 4.0   | 23000 | 1.0545          | 36.7450 | {'rouge1': 0.6977900451765099, 'rouge2': 0.4734910607221403, 'rougeL': 0.6373405033951935, 'rougeLsum': 0.6371420919202282}  | {'score': 63.918132836888965, 'char_order': 6, 'word_order': 0, 'beta': 2} |
+| 1.0935        | 5.0   | 28750 | 1.0538          | 36.7038 | {'rouge1': 0.6978511315129863, 'rouge2': 0.4733012047244315, 'rougeL': 0.6371351829239855, 'rougeLsum': 0.6369801889854168}  | {'score': 63.87115369473548, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
+| 1.0928        | 6.0   | 34500 | 1.0536          | 36.7485 | {'rouge1': 0.6977169592049554, 'rouge2': 0.4734304167965041, 'rougeL': 0.636966108177003, 'rougeLsum': 0.6367749449397957}   | {'score': 63.894445637643784, 'char_order': 6, 'word_order': 0, 'beta': 2} |
+| 1.0918        | 7.0   | 40250 | 1.0536          | 36.7256 | {'rouge1': 0.6977825292445439, 'rouge2': 0.47317224666360513, 'rougeL': 0.6369586014923634, 'rougeLsum': 0.6367120144580565} | {'score': 63.88643397225133, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
+
+
 ### Framework versions
 
 - PEFT 0.10.0