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README.md ADDED
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+ ---
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+ base_model: Tobius/opus-mt-en-lg-finetuned-en-to-lg
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - bleu
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+ model-index:
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+ - name: opus-mt-en-lg-finetuned-en-to-lg-finetuned-en-to-lm
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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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+ # opus-mt-en-lg-finetuned-en-to-lg-finetuned-en-to-lm
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+
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+ This model is a fine-tuned version of [Tobius/opus-mt-en-lg-finetuned-en-to-lg](https://huggingface.co/Tobius/opus-mt-en-lg-finetuned-en-to-lg) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7639
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+ - Bleu: 30.9462
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+ - Gen Len: 21.6305
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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: 0.0001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: linear
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+ - num_epochs: 30
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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 | Bleu | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
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+ | No log | 1.0 | 146 | 3.6537 | 0.5489 | 30.8399 |
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+ | No log | 2.0 | 292 | 3.0866 | 0.5298 | 22.7759 |
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+ | No log | 3.0 | 438 | 2.7528 | 0.8364 | 26.5419 |
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+ | 3.8771 | 4.0 | 584 | 2.4983 | 1.6885 | 25.3966 |
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+ | 3.8771 | 5.0 | 730 | 2.2893 | 2.265 | 23.0296 |
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+ | 3.8771 | 6.0 | 876 | 2.1164 | 3.5594 | 21.9409 |
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+ | 2.5379 | 7.0 | 1022 | 1.9606 | 3.8191 | 22.8325 |
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+ | 2.5379 | 8.0 | 1168 | 1.8145 | 4.7176 | 22.5025 |
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+ | 2.5379 | 9.0 | 1314 | 1.6974 | 5.5036 | 21.7931 |
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+ | 2.5379 | 10.0 | 1460 | 1.5895 | 7.0622 | 21.9483 |
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+ | 2.0088 | 11.0 | 1606 | 1.4934 | 7.9064 | 22.2143 |
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+ | 2.0088 | 12.0 | 1752 | 1.4120 | 8.7831 | 20.9754 |
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+ | 2.0088 | 13.0 | 1898 | 1.3244 | 10.7815 | 21.899 |
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+ | 1.6503 | 14.0 | 2044 | 1.2544 | 11.9959 | 21.835 |
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+ | 1.6503 | 15.0 | 2190 | 1.1843 | 12.9721 | 21.766 |
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+ | 1.6503 | 16.0 | 2336 | 1.1271 | 15.3546 | 21.5542 |
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+ | 1.6503 | 17.0 | 2482 | 1.0670 | 15.9538 | 21.7906 |
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+ | 1.3905 | 18.0 | 2628 | 1.0184 | 19.1229 | 21.9212 |
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+ | 1.3905 | 19.0 | 2774 | 0.9797 | 20.3025 | 21.0148 |
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+ | 1.3905 | 20.0 | 2920 | 0.9358 | 22.3064 | 21.6946 |
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+ | 1.1903 | 21.0 | 3066 | 0.9012 | 24.9192 | 21.3128 |
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+ | 1.1903 | 22.0 | 3212 | 0.8704 | 25.8138 | 21.3202 |
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+ | 1.1903 | 23.0 | 3358 | 0.8481 | 26.8542 | 21.5591 |
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+ | 1.0573 | 24.0 | 3504 | 0.8228 | 28.4838 | 21.3251 |
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+ | 1.0573 | 25.0 | 3650 | 0.8069 | 29.1448 | 21.399 |
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+ | 1.0573 | 26.0 | 3796 | 0.7892 | 29.8567 | 21.5985 |
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+ | 1.0573 | 27.0 | 3942 | 0.7777 | 29.8862 | 21.6404 |
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+ | 0.9649 | 28.0 | 4088 | 0.7703 | 30.9483 | 21.7315 |
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+ | 0.9649 | 29.0 | 4234 | 0.7660 | 30.9831 | 21.6108 |
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+ | 0.9649 | 30.0 | 4380 | 0.7639 | 30.9462 | 21.6305 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ "transformers_version": "4.38.2"
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