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  1. README.md +69 -0
  2. adapter_model.safetensors +1 -1
README.md ADDED
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+ ---
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+ license: cc-by-nc-4.0
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ base_model: facebook/nllb-200-1.3B
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+ metrics:
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+ - bleu
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+ - rouge
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+ model-index:
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+ - name: nllb-200-1.3B-ICFOSS-Hindi_Malayalam_Translator
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # nllb-200-1.3B-ICFOSS-Hindi_Malayalam_Translator
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+
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5883
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+ - Bleu: 32.3133
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+ - Rouge: {'rouge1': 0.4065168353303946, 'rouge2': 0.2762287202150305, 'rougeL': 0.3947284265080875, 'rougeLsum': 0.3952044100349186}
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+ - Chrf: {'score': 69.00192526889488, 'char_order': 6, 'word_order': 0, 'beta': 2}
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge | Chrf |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:----------------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------:|
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+ | 0.7199 | 1.0 | 4698 | 0.6215 | 29.8169 | {'rouge1': 0.405762448982788, 'rouge2': 0.2722973168668976, 'rougeL': 0.3920717141056125, 'rougeLsum': 0.39226265285587325} | {'score': 67.671645233609, 'char_order': 6, 'word_order': 0, 'beta': 2} |
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+ | 0.6269 | 2.0 | 9396 | 0.5960 | 31.5169 | {'rouge1': 0.4074341383663418, 'rouge2': 0.2754310444010575, 'rougeL': 0.3950826699767377, 'rougeLsum': 0.3954069337543914} | {'score': 68.50668767972792, 'char_order': 6, 'word_order': 0, 'beta': 2} |
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+ | 0.5962 | 3.0 | 14094 | 0.5891 | 32.4131 | {'rouge1': 0.4065168353303946, 'rouge2': 0.2774409260882534, 'rougeL': 0.3949096085748628, 'rougeLsum': 0.39546625690693493} | {'score': 68.94783702655978, 'char_order': 6, 'word_order': 0, 'beta': 2} |
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+ | 0.5855 | 4.0 | 18792 | 0.5882 | 32.4648 | {'rouge1': 0.4065168353303946, 'rouge2': 0.2762287202150305, 'rougeL': 0.3947284265080875, 'rougeLsum': 0.3952044100349186} | {'score': 69.10087499970177, 'char_order': 6, 'word_order': 0, 'beta': 2} |
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+ | 0.5835 | 5.0 | 23490 | 0.5883 | 32.3133 | {'rouge1': 0.4065168353303946, 'rouge2': 0.2762287202150305, 'rougeL': 0.3947284265080875, 'rougeLsum': 0.3952044100349186} | {'score': 69.00192526889488, 'char_order': 6, 'word_order': 0, 'beta': 2} |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.10.0
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+ - Transformers 4.40.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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