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nllb-200-distilled-1.3B-finetuned-finetuned-finetuned-finetuned

PyTorch
m2m_100
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  1. README.md +71 -0
  2. generation_config.json +8 -0
  3. pytorch_model-00001-of-00002.bin +3 -0
  4. pytorch_model-00002-of-00002.bin +3 -0
  5. pytorch_model.bin.index.json +1023 -0
README.md ADDED
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+ ---
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+ license: cc-by-nc-4.0
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+ base_model: KevinKibe/nllb-200-distilled-1.3B-finetuned-finetuned-finetuned
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: nllb-200-distilled-1.3B-finetuned-finetuned-finetuned-finetuned
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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-distilled-1.3B-finetuned-finetuned-finetuned-finetuned
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+
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+ This model is a fine-tuned version of [KevinKibe/nllb-200-distilled-1.3B-finetuned-finetuned-finetuned](https://huggingface.co/KevinKibe/nllb-200-distilled-1.3B-finetuned-finetuned-finetuned) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3966
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+ - Rouge: 0.2713
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+ - Gen Len: 22.5
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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: 5e-05
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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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+ - training_steps: 2000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge | Gen Len |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|:-------:|
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+ | 0.0032 | 200.0 | 200 | 0.4363 | 0.2835 | 22.0 |
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+ | 0.0003 | 400.0 | 400 | 0.3573 | 0.2713 | 22.5 |
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+ | 0.0 | 600.0 | 600 | 0.3756 | 0.2762 | 19.5 |
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+ | 0.0 | 800.0 | 800 | 0.3805 | 0.2762 | 19.5 |
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+ | 0.0 | 1000.0 | 1000 | 0.3809 | 0.2762 | 19.5 |
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+ | 0.0 | 1200.0 | 1200 | 0.3848 | 0.2762 | 19.5 |
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+ | 0.0 | 1400.0 | 1400 | 0.3964 | 0.2713 | 22.5 |
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+ | 0.0 | 1600.0 | 1600 | 0.3961 | 0.2713 | 22.5 |
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+ | 0.0 | 1800.0 | 1800 | 0.3964 | 0.2713 | 22.5 |
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+ | 0.0 | 2000.0 | 2000 | 0.3966 | 0.2713 | 22.5 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.2
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+ - Pytorch 2.2.2+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.15.2
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+ "transformers_version": "4.39.2"
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+ }
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