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ruBert-base-finetuned-pos

Token Classification
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Russian
bert
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  1. README.md +11 -51
  2. model.safetensors +1 -1
  3. runs/Mar22_09-07-04_81a9b4ddc734/events.out.tfevents.1711098425.81a9b4ddc734.13612.2 +3 -0
  4. runs/Mar22_09-07-04_81a9b4ddc734/events.out.tfevents.1711100104.81a9b4ddc734.13612.3 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ai-forever/ruBert-base](https://huggingface.co/ai-forever/ruBert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8209
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- - Precision: 0.5
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- - Recall: 0.0071
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- - F1: 0.0140
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- - Accuracy: 0.2141
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  ## Model description
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@@ -49,57 +49,17 @@ The following hyperparameters were used during training:
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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: 45
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  ### Training results
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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 | 1 | 3.6999 | 0.0261 | 0.0260 | 0.0260 | 0.0107 |
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- | No log | 2.0 | 2 | 3.4111 | 0.0382 | 0.0355 | 0.0368 | 0.0043 |
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- | No log | 3.0 | 3 | 3.1202 | 0.0645 | 0.0473 | 0.0546 | 0.0043 |
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- | No log | 4.0 | 4 | 2.8246 | 0.0625 | 0.0307 | 0.0412 | 0.0021 |
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- | No log | 5.0 | 5 | 2.5289 | 0.0426 | 0.0095 | 0.0155 | 0.0 |
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- | No log | 6.0 | 6 | 2.2452 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 7.0 | 7 | 1.9900 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 8.0 | 8 | 1.7794 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 9.0 | 9 | 1.6144 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 10.0 | 10 | 1.4867 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 11.0 | 11 | 1.3877 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 12.0 | 12 | 1.3110 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 13.0 | 13 | 1.2515 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 14.0 | 14 | 1.2053 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 15.0 | 15 | 1.1687 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 16.0 | 16 | 1.1389 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 17.0 | 17 | 1.1135 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 18.0 | 18 | 1.0908 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 19.0 | 19 | 1.0698 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 20.0 | 20 | 1.0500 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 21.0 | 21 | 1.0312 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 22.0 | 22 | 1.0132 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 23.0 | 23 | 0.9962 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 24.0 | 24 | 0.9801 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 25.0 | 25 | 0.9648 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 26.0 | 26 | 0.9504 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 27.0 | 27 | 0.9368 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 28.0 | 28 | 0.9241 | 0.0 | 0.0 | 0.0 | 0.0043 |
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- | No log | 29.0 | 29 | 0.9121 | 0.0 | 0.0 | 0.0 | 0.0128 |
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- | No log | 30.0 | 30 | 0.9009 | 0.0 | 0.0 | 0.0 | 0.0236 |
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- | No log | 31.0 | 31 | 0.8905 | 0.0 | 0.0 | 0.0 | 0.0385 |
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- | No log | 32.0 | 32 | 0.8809 | 0.0 | 0.0 | 0.0 | 0.0578 |
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- | No log | 33.0 | 33 | 0.8720 | 0.0 | 0.0 | 0.0 | 0.0792 |
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- | No log | 34.0 | 34 | 0.8639 | 0.0 | 0.0 | 0.0 | 0.1006 |
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- | No log | 35.0 | 35 | 0.8566 | 0.0 | 0.0 | 0.0 | 0.1199 |
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- | No log | 36.0 | 36 | 0.8500 | 0.0 | 0.0 | 0.0 | 0.1478 |
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- | No log | 37.0 | 37 | 0.8440 | 0.5 | 0.0024 | 0.0047 | 0.1713 |
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- | No log | 38.0 | 38 | 0.8388 | 0.5 | 0.0024 | 0.0047 | 0.1863 |
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- | No log | 39.0 | 39 | 0.8343 | 0.5 | 0.0024 | 0.0047 | 0.1949 |
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- | No log | 40.0 | 40 | 0.8304 | 0.5 | 0.0047 | 0.0094 | 0.2034 |
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- | No log | 41.0 | 41 | 0.8272 | 0.5 | 0.0047 | 0.0094 | 0.2099 |
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- | No log | 42.0 | 42 | 0.8247 | 0.5 | 0.0071 | 0.0140 | 0.2120 |
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- | No log | 43.0 | 43 | 0.8228 | 0.5 | 0.0071 | 0.0140 | 0.2120 |
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- | No log | 44.0 | 44 | 0.8215 | 0.5 | 0.0071 | 0.0140 | 0.2141 |
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- | No log | 45.0 | 45 | 0.8209 | 0.5 | 0.0071 | 0.0140 | 0.2141 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [ai-forever/ruBert-base](https://huggingface.co/ai-forever/ruBert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1544
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+ - Precision: 0.8561
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+ - Recall: 0.8723
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+ - F1: 0.8642
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+ - Accuracy: 0.8822
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  ## Model description
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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: 5
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  ### Training results
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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 | 311 | 0.1686 | 0.8380 | 0.8440 | 0.8410 | 0.8565 |
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+ | 0.0464 | 2.0 | 622 | 0.1597 | 0.8462 | 0.8582 | 0.8521 | 0.8715 |
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+ | 0.0464 | 3.0 | 933 | 0.1544 | 0.8561 | 0.8723 | 0.8642 | 0.8822 |
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+ | 0.0046 | 4.0 | 1244 | 0.1564 | 0.8469 | 0.8629 | 0.8548 | 0.8737 |
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+ | 0.0029 | 5.0 | 1555 | 0.1556 | 0.8538 | 0.8700 | 0.8618 | 0.8801 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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