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RuBioRoBERTa_pos

Token Classification
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  1. README.md +109 -0
  2. config.json +38 -0
  3. merges.txt +0 -0
  4. model.safetensors +3 -0
  5. runs/May07_01-03-13_4537e44771aa/events.out.tfevents.1715043794.4537e44771aa.34.6 +3 -0
  6. runs/May07_01-03-13_4537e44771aa/events.out.tfevents.1715045903.4537e44771aa.34.7 +3 -0
  7. special_tokens_map.json +51 -0
  8. tokenizer.json +0 -0
  9. tokenizer_config.json +59 -0
  10. training_args.bin +3 -0
  11. vocab.json +0 -0
README.md ADDED
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+ ---
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+ base_model: alexyalunin/RuBioRoBERTa
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: RuBioRoBERTa_pos
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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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+ # RuBioRoBERTa_pos
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+
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+ This model is a fine-tuned version of [alexyalunin/RuBioRoBERTa](https://huggingface.co/alexyalunin/RuBioRoBERTa) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5510
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+ - Precision: 0.6388
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+ - Recall: 0.5954
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+ - F1: 0.6163
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+ - Accuracy: 0.9111
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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: 4
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+ - eval_batch_size: 8
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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: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 50 | 0.6556 | 0.0 | 0.0 | 0.0 | 0.7611 |
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+ | No log | 2.0 | 100 | 1.2213 | 0.0011 | 0.0019 | 0.0014 | 0.2513 |
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+ | No log | 3.0 | 150 | 0.6117 | 0.0 | 0.0 | 0.0 | 0.7642 |
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+ | No log | 4.0 | 200 | 0.5155 | 0.0135 | 0.0405 | 0.0203 | 0.7884 |
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+ | No log | 5.0 | 250 | 0.4171 | 0.0697 | 0.1715 | 0.0991 | 0.8268 |
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+ | No log | 6.0 | 300 | 0.3536 | 0.1054 | 0.1753 | 0.1317 | 0.8594 |
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+ | No log | 7.0 | 350 | 0.3714 | 0.1638 | 0.2216 | 0.1884 | 0.8685 |
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+ | No log | 8.0 | 400 | 0.2889 | 0.2477 | 0.3622 | 0.2942 | 0.8864 |
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+ | No log | 9.0 | 450 | 0.2943 | 0.2799 | 0.3969 | 0.3283 | 0.8921 |
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+ | 0.452 | 10.0 | 500 | 0.2916 | 0.3823 | 0.4817 | 0.4263 | 0.9011 |
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+ | 0.452 | 11.0 | 550 | 0.3162 | 0.3329 | 0.4817 | 0.3937 | 0.8935 |
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+ | 0.452 | 12.0 | 600 | 0.3245 | 0.3629 | 0.4971 | 0.4195 | 0.9040 |
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+ | 0.452 | 13.0 | 650 | 0.3535 | 0.4022 | 0.4913 | 0.4423 | 0.9021 |
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+ | 0.452 | 14.0 | 700 | 0.3313 | 0.4161 | 0.5588 | 0.4770 | 0.9023 |
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+ | 0.452 | 15.0 | 750 | 0.3560 | 0.4210 | 0.5800 | 0.4878 | 0.9006 |
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+ | 0.452 | 16.0 | 800 | 0.3980 | 0.4125 | 0.6224 | 0.4962 | 0.8905 |
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+ | 0.452 | 17.0 | 850 | 0.3767 | 0.4820 | 0.6455 | 0.5519 | 0.9071 |
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+ | 0.452 | 18.0 | 900 | 0.3947 | 0.4605 | 0.6513 | 0.5395 | 0.9034 |
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+ | 0.452 | 19.0 | 950 | 0.4351 | 0.4395 | 0.5877 | 0.5029 | 0.9066 |
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+ | 0.0844 | 20.0 | 1000 | 0.3581 | 0.4931 | 0.5530 | 0.5213 | 0.9097 |
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+ | 0.0844 | 21.0 | 1050 | 0.4050 | 0.4892 | 0.6108 | 0.5433 | 0.9063 |
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+ | 0.0844 | 22.0 | 1100 | 0.4893 | 0.5504 | 0.5472 | 0.5488 | 0.9076 |
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+ | 0.0844 | 23.0 | 1150 | 0.4173 | 0.4722 | 0.6050 | 0.5304 | 0.9062 |
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+ | 0.0844 | 24.0 | 1200 | 0.4307 | 0.4819 | 0.6146 | 0.5402 | 0.9075 |
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+ | 0.0844 | 25.0 | 1250 | 0.3874 | 0.4977 | 0.6185 | 0.5515 | 0.9151 |
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+ | 0.0844 | 26.0 | 1300 | 0.4591 | 0.5478 | 0.6513 | 0.5951 | 0.9130 |
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+ | 0.0844 | 27.0 | 1350 | 0.3543 | 0.5308 | 0.5973 | 0.5621 | 0.9144 |
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+ | 0.0844 | 28.0 | 1400 | 0.4676 | 0.5380 | 0.5453 | 0.5416 | 0.9187 |
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+ | 0.0844 | 29.0 | 1450 | 0.4169 | 0.5365 | 0.6224 | 0.5763 | 0.9131 |
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+ | 0.0401 | 30.0 | 1500 | 0.4394 | 0.5867 | 0.5607 | 0.5734 | 0.9114 |
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+ | 0.0401 | 31.0 | 1550 | 0.4550 | 0.5446 | 0.6474 | 0.5915 | 0.9166 |
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+ | 0.0401 | 32.0 | 1600 | 0.4592 | 0.5415 | 0.6166 | 0.5766 | 0.9125 |
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+ | 0.0401 | 33.0 | 1650 | 0.5040 | 0.5218 | 0.6455 | 0.5771 | 0.9093 |
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+ | 0.0401 | 34.0 | 1700 | 0.4609 | 0.4295 | 0.6686 | 0.5230 | 0.8989 |
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+ | 0.0401 | 35.0 | 1750 | 0.6256 | 0.4833 | 0.6397 | 0.5506 | 0.8975 |
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+ | 0.0401 | 36.0 | 1800 | 0.4697 | 0.5742 | 0.6185 | 0.5955 | 0.9088 |
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+ | 0.0401 | 37.0 | 1850 | 0.5114 | 0.5645 | 0.6069 | 0.5850 | 0.9139 |
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+ | 0.0401 | 38.0 | 1900 | 0.5884 | 0.6237 | 0.5780 | 0.6 | 0.9088 |
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+ | 0.0401 | 39.0 | 1950 | 0.5022 | 0.5429 | 0.6455 | 0.5898 | 0.9135 |
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+ | 0.0328 | 40.0 | 2000 | 0.4154 | 0.6315 | 0.6339 | 0.6327 | 0.9202 |
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+ | 0.0328 | 41.0 | 2050 | 0.3940 | 0.5519 | 0.6146 | 0.5816 | 0.9145 |
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+ | 0.0328 | 42.0 | 2100 | 0.3374 | 0.5477 | 0.6301 | 0.5860 | 0.9120 |
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+ | 0.0328 | 43.0 | 2150 | 0.5907 | 0.5483 | 0.5029 | 0.5246 | 0.9041 |
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+ | 0.0328 | 44.0 | 2200 | 0.4235 | 0.5606 | 0.6416 | 0.5984 | 0.9145 |
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+ | 0.0328 | 45.0 | 2250 | 0.6646 | 0.0 | 0.0 | 0.0 | 0.7640 |
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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 2.1.2
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+ - Datasets 2.1.0
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+ - Tokenizers 0.15.2
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