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--- |
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license: cc-by-nc-4.0 |
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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: NNLB-alt-en-bleu-ht |
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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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# NNLB-alt-en-bleu-ht |
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This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4011 |
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- Bleu: 40.828 |
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- Gen Len: 26.385 |
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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: 0.0001 |
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- train_batch_size: 14 |
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- eval_batch_size: 14 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
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| 2.0036 | 1.0 | 799 | 1.4377 | 25.1487 | 25.036 | |
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| 1.2584 | 2.0 | 1598 | 1.3276 | 29.603 | 25.723 | |
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| 1.0147 | 3.0 | 2397 | 1.3204 | 31.3967 | 25.776 | |
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| 0.7379 | 4.0 | 3196 | 1.3678 | 32.4951 | 25.266 | |
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| 0.6228 | 5.0 | 3995 | 1.4250 | 34.6087 | 26.083 | |
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| 0.4327 | 6.0 | 4794 | 1.5342 | 36.6073 | 26.174 | |
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| 0.3437 | 7.0 | 5593 | 1.5952 | 37.7791 | 26.265 | |
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| 0.2689 | 8.0 | 6392 | 1.6993 | 38.16 | 26.376 | |
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| 0.2029 | 9.0 | 7191 | 1.7994 | 39.433 | 26.766 | |
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| 0.1711 | 10.0 | 7990 | 1.8893 | 39.2816 | 26.574 | |
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| 0.1214 | 11.0 | 8789 | 1.9661 | 39.5599 | 26.687 | |
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| 0.1017 | 12.0 | 9588 | 1.9928 | 39.7801 | 26.845 | |
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| 0.0855 | 13.0 | 10387 | 2.0508 | 39.8043 | 26.641 | |
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| 0.0679 | 14.0 | 11186 | 2.0998 | 40.3389 | 26.526 | |
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| 0.06 | 15.0 | 11985 | 2.1350 | 40.0964 | 26.395 | |
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| 0.0475 | 16.0 | 12784 | 2.1676 | 40.1536 | 26.614 | |
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| 0.0407 | 17.0 | 13583 | 2.2040 | 40.298 | 26.494 | |
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| 0.0347 | 18.0 | 14382 | 2.2294 | 40.5207 | 26.612 | |
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| 0.0315 | 19.0 | 15181 | 2.2484 | 40.3323 | 26.53 | |
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| 0.0286 | 20.0 | 15980 | 2.2828 | 40.3167 | 26.718 | |
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| 0.0241 | 21.0 | 16779 | 2.3015 | 40.0766 | 26.306 | |
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| 0.0213 | 22.0 | 17578 | 2.3267 | 40.477 | 26.457 | |
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| 0.0183 | 23.0 | 18377 | 2.3410 | 40.4013 | 26.406 | |
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| 0.0164 | 24.0 | 19176 | 2.3457 | 40.3643 | 26.534 | |
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| 0.0157 | 25.0 | 19975 | 2.3533 | 40.3967 | 26.506 | |
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| 0.0133 | 26.0 | 20774 | 2.3734 | 40.7786 | 26.38 | |
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| 0.0119 | 27.0 | 21573 | 2.3750 | 40.8653 | 26.525 | |
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| 0.0106 | 28.0 | 22372 | 2.3896 | 40.8371 | 26.503 | |
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| 0.0095 | 29.0 | 23171 | 2.3893 | 40.831 | 26.398 | |
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| 0.0094 | 30.0 | 23970 | 2.4011 | 40.828 | 26.385 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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