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ICFOSS_Malayalam_English_Translator
arun3936/ICFOSS_Malayalam_English_Translator
ICFOSS_Malayalam_English_Translator is a machine learning model from arun3936. 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
- Dec 29, 2023
- Updated
- Mar 20, 2024
- SHA
- e88d8a6e
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-200-3.3B-Malayalam_English_Translationt_nllb6
This model is a fine-tuned version of facebook/nllb-200-3.3B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0031
- Bleu: 37.4644
- Rouge: {'rouge1': 0.6947858221991348, 'rouge2': 0.47528501248267296, 'rougeL': 0.643592904253675, 'rougeLsum': 0.6438336053077185}
- Chrf: {'score': 63.562323751931785, '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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|
| 1.1299 | 1.0 | 9400 | 1.0473 | 35.4794 | {'rouge1': 0.6827076206592405, 'rouge2': 0.4567713815837643, 'rougeL': 0.6303031579761407, 'rougeLsum': 0.6303637744842896} | {'score': 62.07772367684291, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 1.0391 | 2.0 | 18800 | 1.0172 | 36.5551 | {'rouge1': 0.6898802619220783, 'rouge2': 0.4678566080033477, 'rougeL': 0.6376152634193879, 'rougeLsum': 0.6378050818770977} | {'score': 62.79493404105809, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 0.9772 | 3.0 | 28200 | 1.0047 | 37.1999 | {'rouge1': 0.6940761673780116, 'rouge2': 0.4729467289482048, 'rougeL': 0.6422221741064402, 'rougeLsum': 0.6423854506325695} | {'score': 63.383659426629755, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 0.9322 | 4.0 | 37600 | 1.0021 | 37.3505 | {'rouge1': 0.6946177869994575, 'rouge2': 0.47460537713160267, 'rougeL': 0.643360432984222, 'rougeLsum': 0.6434552650502989} | {'score': 63.44418689943615, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 0.9109 | 5.0 | 47000 | 1.0031 | 37.4644 | {'rouge1': 0.6947858221991348, 'rouge2': 0.47528501248267296, 'rougeL': 0.643592904253675, 'rougeLsum': 0.6438336053077185} | {'score': 63.562323751931785, 'char_order': 6, 'word_order': 0, 'beta': 2} |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.36.1
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.15.0
- Library
- peft
- License
- cc-by-nc-4.0
- Created
- Dec 29, 2023
- Updated
- Mar 20, 2024