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rubert-base-cased_neg

Token Classification
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Files changed (10) hide show
  1. README.md +146 -0
  2. config.json +42 -0
  3. model.safetensors +3 -0
  4. runs/May07_08-37-16_cc926814451a/events.out.tfevents.1715071037.cc926814451a.35.4 +3 -0
  5. runs/May07_08-37-16_cc926814451a/events.out.tfevents.1715072393.cc926814451a.35.5 +3 -0
  6. special_tokens_map.json +7 -0
  7. tokenizer.json +0 -0
  8. tokenizer_config.json +58 -0
  9. training_args.bin +3 -0
  10. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ base_model: DeepPavlov/rubert-base-cased
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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: rubert-base-cased_neg
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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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+ # rubert-base-cased_neg
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+
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+ This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6290
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+ - Precision: 0.5977
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+ - Recall: 0.6106
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+ - F1: 0.6041
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+ - Accuracy: 0.8995
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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 | 1.11 | 50 | 0.6820 | 0.0 | 0.0 | 0.0 | 0.7747 |
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+ | No log | 2.22 | 100 | 0.5532 | 0.0489 | 0.0212 | 0.0296 | 0.8040 |
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+ | No log | 3.33 | 150 | 0.4231 | 0.1320 | 0.1004 | 0.1140 | 0.8397 |
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+ | No log | 4.44 | 200 | 0.3736 | 0.2200 | 0.1873 | 0.2023 | 0.8576 |
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+ | No log | 5.56 | 250 | 0.3511 | 0.3096 | 0.2606 | 0.2830 | 0.8713 |
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+ | No log | 6.67 | 300 | 0.2976 | 0.3635 | 0.4498 | 0.4021 | 0.8833 |
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+ | No log | 7.78 | 350 | 0.2713 | 0.3793 | 0.4942 | 0.4292 | 0.8925 |
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+ | No log | 8.89 | 400 | 0.2569 | 0.4174 | 0.5753 | 0.4838 | 0.9016 |
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+ | No log | 10.0 | 450 | 0.2599 | 0.4687 | 0.5772 | 0.5173 | 0.9031 |
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+ | 0.389 | 11.11 | 500 | 0.2775 | 0.5008 | 0.5849 | 0.5396 | 0.9084 |
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+ | 0.389 | 12.22 | 550 | 0.3123 | 0.4257 | 0.6641 | 0.5189 | 0.8834 |
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+ | 0.389 | 13.33 | 600 | 0.3271 | 0.5036 | 0.5425 | 0.5223 | 0.9064 |
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+ | 0.389 | 14.44 | 650 | 0.3390 | 0.5328 | 0.5174 | 0.5250 | 0.9016 |
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+ | 0.389 | 15.56 | 700 | 0.3688 | 0.4788 | 0.6313 | 0.5445 | 0.8988 |
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+ | 0.389 | 16.67 | 750 | 0.4260 | 0.4942 | 0.6583 | 0.5646 | 0.8997 |
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+ | 0.389 | 17.78 | 800 | 0.3622 | 0.5217 | 0.6042 | 0.5599 | 0.9106 |
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+ | 0.389 | 18.89 | 850 | 0.4054 | 0.5266 | 0.6120 | 0.5661 | 0.9105 |
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+ | 0.389 | 20.0 | 900 | 0.3988 | 0.5070 | 0.6255 | 0.5601 | 0.9049 |
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+ | 0.389 | 21.11 | 950 | 0.4422 | 0.5281 | 0.5444 | 0.5361 | 0.9093 |
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+ | 0.0777 | 22.22 | 1000 | 0.4207 | 0.5635 | 0.5656 | 0.5645 | 0.9117 |
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+ | 0.0777 | 23.33 | 1050 | 0.4721 | 0.5505 | 0.5792 | 0.5644 | 0.9130 |
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+ | 0.0777 | 24.44 | 1100 | 0.4261 | 0.5379 | 0.6158 | 0.5743 | 0.9114 |
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+ | 0.0777 | 25.56 | 1150 | 0.5339 | 0.6157 | 0.5290 | 0.5691 | 0.9 |
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+ | 0.0777 | 26.67 | 1200 | 0.3761 | 0.4949 | 0.6544 | 0.5636 | 0.9036 |
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+ | 0.0777 | 27.78 | 1250 | 0.4250 | 0.5650 | 0.5792 | 0.5720 | 0.9110 |
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+ | 0.0777 | 28.89 | 1300 | 0.3790 | 0.5731 | 0.6429 | 0.6060 | 0.9193 |
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+ | 0.0777 | 30.0 | 1350 | 0.5330 | 0.5942 | 0.5907 | 0.5924 | 0.9076 |
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+ | 0.0777 | 31.11 | 1400 | 0.4419 | 0.5957 | 0.5888 | 0.5922 | 0.9180 |
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+ | 0.0777 | 32.22 | 1450 | 0.5531 | 0.6008 | 0.5695 | 0.5847 | 0.9088 |
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+ | 0.0362 | 33.33 | 1500 | 0.4544 | 0.5231 | 0.6564 | 0.5822 | 0.9135 |
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+ | 0.0362 | 34.44 | 1550 | 0.4990 | 0.5695 | 0.5772 | 0.5733 | 0.9082 |
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+ | 0.0362 | 35.56 | 1600 | 0.4040 | 0.5709 | 0.5753 | 0.5731 | 0.9086 |
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+ | 0.0362 | 36.67 | 1650 | 0.3807 | 0.5989 | 0.6255 | 0.6119 | 0.9123 |
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+ | 0.0362 | 37.78 | 1700 | 0.5088 | 0.5996 | 0.6100 | 0.6048 | 0.9139 |
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+ | 0.0362 | 38.89 | 1750 | 0.4525 | 0.6151 | 0.5985 | 0.6067 | 0.9189 |
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+ | 0.0362 | 40.0 | 1800 | 0.3787 | 0.6184 | 0.6100 | 0.6142 | 0.9211 |
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+ | 0.0362 | 41.11 | 1850 | 0.3974 | 0.6097 | 0.5849 | 0.5970 | 0.9162 |
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+ | 0.0362 | 42.22 | 1900 | 0.3944 | 0.5762 | 0.6274 | 0.6007 | 0.9148 |
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+ | 0.0362 | 43.33 | 1950 | 0.3865 | 0.5124 | 0.6795 | 0.5842 | 0.9022 |
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+ | 0.0264 | 44.44 | 2000 | 0.4583 | 0.5462 | 0.6274 | 0.5840 | 0.9169 |
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+ | 0.0264 | 45.56 | 2050 | 0.4640 | 0.5635 | 0.6429 | 0.6005 | 0.9105 |
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+ | 0.0264 | 46.67 | 2100 | 0.5028 | 0.5945 | 0.5830 | 0.5887 | 0.9128 |
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+ | 0.0264 | 47.78 | 2150 | 0.3917 | 0.6267 | 0.6255 | 0.6261 | 0.9221 |
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+ | 0.0264 | 48.89 | 2200 | 0.4833 | 0.6214 | 0.6274 | 0.6244 | 0.9138 |
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+ | 0.0264 | 50.0 | 2250 | 0.4147 | 0.6130 | 0.6390 | 0.6257 | 0.9190 |
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+ | 0.0264 | 51.11 | 2300 | 0.4455 | 0.6546 | 0.5927 | 0.6221 | 0.9185 |
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+ | 0.0264 | 52.22 | 2350 | 0.4575 | 0.6138 | 0.6351 | 0.6243 | 0.9180 |
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+ | 0.0264 | 53.33 | 2400 | 0.7707 | 0.3732 | 0.6815 | 0.4822 | 0.8354 |
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+ | 0.0264 | 54.44 | 2450 | 0.4440 | 0.6015 | 0.6236 | 0.6123 | 0.9130 |
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+ | 0.0248 | 55.56 | 2500 | 0.4815 | 0.5739 | 0.6448 | 0.6073 | 0.9124 |
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+ | 0.0248 | 56.67 | 2550 | 0.3971 | 0.6204 | 0.6467 | 0.6333 | 0.9227 |
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+ | 0.0248 | 57.78 | 2600 | 0.4770 | 0.6208 | 0.6100 | 0.6154 | 0.9193 |
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+ | 0.0248 | 58.89 | 2650 | 0.5450 | 0.6699 | 0.5367 | 0.5959 | 0.9109 |
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+ | 0.0248 | 60.0 | 2700 | 0.5033 | 0.5439 | 0.6332 | 0.5852 | 0.9019 |
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+ | 0.0248 | 61.11 | 2750 | 0.5185 | 0.5187 | 0.6699 | 0.5847 | 0.9010 |
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+ | 0.0248 | 62.22 | 2800 | 0.4277 | 0.6627 | 0.6371 | 0.6496 | 0.9194 |
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+ | 0.0248 | 63.33 | 2850 | 0.4688 | 0.4869 | 0.6467 | 0.5556 | 0.9066 |
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+ | 0.0248 | 64.44 | 2900 | 0.4779 | 0.6135 | 0.6313 | 0.6223 | 0.9153 |
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+ | 0.0248 | 65.56 | 2950 | 0.5012 | 0.5852 | 0.6100 | 0.5974 | 0.9079 |
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+ | 0.0232 | 66.67 | 3000 | 0.4788 | 0.5259 | 0.6081 | 0.5640 | 0.9052 |
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+ | 0.0232 | 67.78 | 3050 | 0.4556 | 0.5726 | 0.6544 | 0.6108 | 0.9099 |
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+ | 0.0232 | 68.89 | 3100 | 0.5026 | 0.608 | 0.5869 | 0.5972 | 0.9091 |
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+ | 0.0232 | 70.0 | 3150 | 0.8153 | 0.3071 | 0.7143 | 0.4295 | 0.7567 |
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+ | 0.0232 | 71.11 | 3200 | 0.4670 | 0.6169 | 0.6062 | 0.6115 | 0.9113 |
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+ | 0.0232 | 72.22 | 3250 | 0.5249 | 0.5727 | 0.6313 | 0.6006 | 0.9068 |
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+ | 0.0232 | 73.33 | 3300 | 0.4343 | 0.6085 | 0.6390 | 0.6234 | 0.9162 |
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+ | 0.0232 | 74.44 | 3350 | 0.5067 | 0.6364 | 0.5811 | 0.6075 | 0.9135 |
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+ | 0.0232 | 75.56 | 3400 | 0.4415 | 0.5812 | 0.6429 | 0.6104 | 0.9149 |
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+ | 0.0232 | 76.67 | 3450 | 0.4052 | 0.5757 | 0.6313 | 0.6022 | 0.9137 |
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+ | 0.0266 | 77.78 | 3500 | 0.5119 | 0.5233 | 0.5425 | 0.5327 | 0.9038 |
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+ | 0.0266 | 78.89 | 3550 | 0.4689 | 0.5945 | 0.5888 | 0.5917 | 0.9145 |
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+ | 0.0266 | 80.0 | 3600 | 0.3973 | 0.5609 | 0.6313 | 0.5940 | 0.9154 |
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+ | 0.0266 | 81.11 | 3650 | 0.4848 | 0.5947 | 0.6486 | 0.6205 | 0.9181 |
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+ | 0.0266 | 82.22 | 3700 | 0.4825 | 0.5877 | 0.6274 | 0.6069 | 0.9160 |
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+ | 0.0266 | 83.33 | 3750 | 0.5193 | 0.5138 | 0.6467 | 0.5726 | 0.9 |
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+ | 0.0266 | 84.44 | 3800 | 0.5344 | 0.5777 | 0.5811 | 0.5794 | 0.9107 |
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+ | 0.0266 | 85.56 | 3850 | 0.5227 | 0.6591 | 0.5637 | 0.6077 | 0.9107 |
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+ | 0.0266 | 86.67 | 3900 | 0.4490 | 0.5176 | 0.6255 | 0.5664 | 0.9097 |
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+ | 0.0266 | 87.78 | 3950 | 0.6307 | 0.6464 | 0.5541 | 0.5967 | 0.9068 |
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+ | 0.029 | 88.89 | 4000 | 0.4432 | 0.5667 | 0.5985 | 0.5822 | 0.9099 |
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+ | 0.029 | 90.0 | 4050 | 0.4822 | 0.5148 | 0.6371 | 0.5695 | 0.9018 |
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+ | 0.029 | 91.11 | 4100 | 0.4706 | 0.5966 | 0.6023 | 0.5994 | 0.9128 |
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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
config.json ADDED
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+ {
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+ "_name_or_path": "DeepPavlov/rubert-base-cased",
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+ "BertForTokenClassification"
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+ "hidden_act": "gelu",
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "O",
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+ "1": "B-symp",
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+ "2": "I-symp"
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+ "label2id": {
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.2",
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