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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-distilled-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-distilled-1.3B-ICFOSS-Malayalam_Tamil_Translation1 |
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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-distilled-1.3B-ICFOSS-Malayalam_Tamil_Translation1 |
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This model is a fine-tuned version of [facebook/nllb-200-distilled-1.3B](https://huggingface.co/facebook/nllb-200-distilled-1.3B) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9585 |
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- Bleu: 27.2186 |
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- Rouge: {'rouge1': 0.24019241472720237, 'rouge2': 0.11743746052802109, 'rougeL': 0.23538895581779812, 'rougeLsum': 0.23566947893424423} |
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- Chrf: {'score': 61.354962127257075, '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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| 1.0887 | 1.0 | 3200 | 0.9812 | 26.4453 | {'rouge1': 0.23999162519568762, 'rouge2': 0.11750820308459373, 'rougeL': 0.2354759340604931, 'rougeLsum': 0.23574425317949493} | {'score': 60.78556495445389, 'char_order': 6, 'word_order': 0, 'beta': 2} | |
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| 1.0235 | 2.0 | 6400 | 0.9633 | 27.2057 | {'rouge1': 0.23965959444048868, 'rouge2': 0.11732010332857629, 'rougeL': 0.2348755068042092, 'rougeLsum': 0.2350956429627365} | {'score': 61.143671039500624, 'char_order': 6, 'word_order': 0, 'beta': 2} | |
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| 1.0073 | 3.0 | 9600 | 0.9592 | 27.2471 | {'rouge1': 0.24051300083618463, 'rouge2': 0.11760625620421375, 'rougeL': 0.23594757428338253, 'rougeLsum': 0.23612557860955713} | {'score': 61.30740344086827, 'char_order': 6, 'word_order': 0, 'beta': 2} | |
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| 1.0022 | 4.0 | 12800 | 0.9587 | 27.2024 | {'rouge1': 0.24037345843038344, 'rouge2': 0.1174835459617575, 'rougeL': 0.2356757544571015, 'rougeLsum': 0.23591228047430784} | {'score': 61.34302070824752, 'char_order': 6, 'word_order': 0, 'beta': 2} | |
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| 1.0008 | 5.0 | 16000 | 0.9585 | 27.2186 | {'rouge1': 0.24019241472720237, 'rouge2': 0.11743746052802109, 'rougeL': 0.23538895581779812, 'rougeLsum': 0.23566947893424423} | {'score': 61.354962127257075, '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 4.39.3 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.15.0 |
