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nllb-200-1.3B-ICFOSS-Hindi_Malayalam_Translator
ArunIcfoss/nllb-200-1.3B-ICFOSS-Hindi_Malayalam_Translator
nllb-200-1.3B-ICFOSS-Hindi_Malayalam_Translator is a machine learning model from ArunIcfoss. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- cc-by-nc-4.0
- Access
- Public
- Created
- Aug 22, 2024
- Updated
- Aug 23, 2024
- SHA
- ac0c4ae4
Base models
Model card
From the Hugging Face model README
<!-- 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-Hindi_Malayalam_Translator
This model is a fine-tuned version of facebook/nllb-200-1.3B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5883
- Bleu: 32.3133
- Rouge: {'rouge1': 0.4065168353303946, 'rouge2': 0.2762287202150305, 'rougeL': 0.3947284265080875, 'rougeLsum': 0.3952044100349186}
- Chrf: {'score': 69.00192526889488, '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 |
|---|---|---|---|---|---|---|
| 0.7199 | 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} |
| 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} |
| 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} |
| 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} |
| 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} |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Library
- peft
- License
- cc-by-nc-4.0
- Created
- Aug 22, 2024
- Updated
- Aug 23, 2024