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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_Malayalam_Tamil_Translator |
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results: [] |
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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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# nllb-200-1.3B-ICFOSS_Malayalam_Tamil_Translator |
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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: 0.8336 |
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- Bleu: 30.1755 |
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- Rouge: {'rouge1': 0.27813852813852813, 'rouge2': 0.14151205936920222, 'rougeL': 0.268193413729128, 'rougeLsum': 0.2691068851783137} |
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- Chrf: {'score': 66.57581227024936, 'char_order': 6, 'word_order': 0, 'beta': 2} |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge | Chrf | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-----------------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------:| |
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| 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} | |
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| 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} | |
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| 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} | |
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| 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} | |
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| 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} | |
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### Framework versions |
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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 |
