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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: facebook/m2m100_1.2B
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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: cs_m2m_2e-5_50_v0.2
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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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+ # cs_m2m_2e-5_50_v0.2
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+
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+ This model is a fine-tuned version of [facebook/m2m100_1.2B](https://huggingface.co/facebook/m2m100_1.2B) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 6.9907
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+ - Bleu: 0.0
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+ - Gen Len: 5.0
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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: 2e-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: linear
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+ - num_epochs: 50
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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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+ | 4.7756 | 1.0 | 6 | 6.9340 | 0.0 | 5.0 |
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+ | 3.9022 | 2.0 | 12 | 6.9354 | 0.0 | 5.0 |
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+ | 5.0741 | 3.0 | 18 | 6.9379 | 0.0 | 5.0 |
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+ | 4.4159 | 4.0 | 24 | 6.9402 | 0.0 | 5.0 |
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+ | 3.6725 | 5.0 | 30 | 6.9430 | 0.0 | 5.0 |
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+ | 4.3425 | 6.0 | 36 | 6.9461 | 0.0 | 5.0 |
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+ | 4.5332 | 7.0 | 42 | 6.9481 | 0.0 | 5.0 |
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+ | 4.5802 | 8.0 | 48 | 6.9509 | 0.0 | 5.0 |
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+ | 4.3489 | 9.0 | 54 | 6.9525 | 0.0 | 5.0 |
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+ | 4.5023 | 10.0 | 60 | 6.9545 | 0.0 | 5.0 |
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+ | 4.5163 | 11.0 | 66 | 6.9582 | 0.0 | 5.0 |
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+ | 3.811 | 12.0 | 72 | 6.9592 | 0.0 | 5.0 |
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+ | 4.4632 | 13.0 | 78 | 6.9608 | 0.0 | 5.0 |
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+ | 4.5768 | 14.0 | 84 | 6.9621 | 0.0 | 5.0 |
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+ | 4.9377 | 15.0 | 90 | 6.9637 | 0.0 | 5.0 |
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+ | 4.5133 | 16.0 | 96 | 6.9650 | 0.0 | 5.0 |
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+ | 4.6817 | 17.0 | 102 | 6.9650 | 0.0 | 5.0 |
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+ | 4.7848 | 18.0 | 108 | 6.9658 | 0.0 | 5.0 |
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+ | 4.1093 | 19.0 | 114 | 6.9671 | 0.0 | 5.0 |
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+ | 4.5681 | 20.0 | 120 | 6.9690 | 0.0 | 5.0 |
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+ | 4.7043 | 21.0 | 126 | 6.9708 | 0.0 | 5.0 |
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+ | 4.0004 | 22.0 | 132 | 6.9720 | 0.0 | 5.0 |
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+ | 4.9032 | 23.0 | 138 | 6.9723 | 0.0 | 5.0 |
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+ | 4.5895 | 24.0 | 144 | 6.9722 | 0.0 | 5.0 |
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+ | 4.3594 | 25.0 | 150 | 6.9732 | 0.0 | 5.0 |
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+ | 4.8269 | 26.0 | 156 | 6.9755 | 0.0 | 5.0 |
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+ | 4.4823 | 27.0 | 162 | 6.9776 | 0.0 | 5.0 |
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+ | 4.6239 | 28.0 | 168 | 6.9794 | 0.0 | 5.0 |
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+ | 4.1998 | 29.0 | 174 | 6.9804 | 0.0 | 5.0 |
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+ | 3.9999 | 30.0 | 180 | 6.9819 | 0.0 | 5.0 |
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+ | 4.5411 | 31.0 | 186 | 6.9831 | 0.0 | 5.0 |
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+ | 4.3902 | 32.0 | 192 | 6.9841 | 0.0 | 5.0 |
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+ | 5.4393 | 33.0 | 198 | 6.9849 | 0.0 | 5.0 |
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+ | 4.5883 | 34.0 | 204 | 6.9856 | 0.0 | 5.0 |
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+ | 4.2695 | 35.0 | 210 | 6.9862 | 0.0 | 5.0 |
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+ | 5.4745 | 36.0 | 216 | 6.9866 | 0.0 | 5.0 |
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+ | 4.8483 | 37.0 | 222 | 6.9871 | 0.0 | 5.0 |
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+ | 4.9538 | 38.0 | 228 | 6.9879 | 0.0 | 5.0 |
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+ | 4.6334 | 39.0 | 234 | 6.9887 | 0.0 | 5.0 |
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+ | 4.1038 | 40.0 | 240 | 6.9894 | 0.0 | 5.0 |
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+ | 5.501 | 41.0 | 246 | 6.9900 | 0.0 | 5.0 |
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+ | 4.445 | 42.0 | 252 | 6.9905 | 0.0 | 5.0 |
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+ | 3.8749 | 43.0 | 258 | 6.9906 | 0.0 | 5.0 |
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+ | 3.9839 | 44.0 | 264 | 6.9907 | 0.0 | 5.0 |
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+ | 4.4551 | 45.0 | 270 | 6.9907 | 0.0 | 5.0 |
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+ | 4.5297 | 46.0 | 276 | 6.9907 | 0.0 | 5.0 |
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+ | 4.7603 | 47.0 | 282 | 6.9906 | 0.0 | 5.0 |
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+ | 4.7698 | 48.0 | 288 | 6.9907 | 0.0 | 5.0 |
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+ | 4.3381 | 49.0 | 294 | 6.9907 | 0.0 | 5.0 |
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+ | 4.6124 | 50.0 | 300 | 6.9907 | 0.0 | 5.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 1.13.1+cu117
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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