| --- |
| license: apache-2.0 |
| base_model: DmitryPogrebnoy/MedRuRobertaLarge |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: MedRuRobertaLarge_neg |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # MedRuRobertaLarge_neg |
| |
| This model is a fine-tuned version of [DmitryPogrebnoy/MedRuRobertaLarge](https://huggingface.co/DmitryPogrebnoy/MedRuRobertaLarge) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6996 |
| - Precision: 0.5225 |
| - Recall: 0.5788 |
| - F1: 0.5492 |
| - Accuracy: 0.8955 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 100 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 50 | 0.6906 | 0.0175 | 0.0019 | 0.0035 | 0.7724 | |
| | No log | 2.0 | 100 | 0.7240 | 0.0526 | 0.0019 | 0.0037 | 0.7756 | |
| | No log | 3.0 | 150 | 0.5668 | 0.0407 | 0.0289 | 0.0338 | 0.7668 | |
| | No log | 4.0 | 200 | 0.4358 | 0.1326 | 0.1522 | 0.1417 | 0.8236 | |
| | No log | 5.0 | 250 | 0.3509 | 0.1932 | 0.2177 | 0.2047 | 0.8573 | |
| | No log | 6.0 | 300 | 0.2961 | 0.3339 | 0.3699 | 0.3510 | 0.8862 | |
| | No log | 7.0 | 350 | 0.3715 | 0.4073 | 0.3642 | 0.3845 | 0.8820 | |
| | No log | 8.0 | 400 | 0.2778 | 0.4511 | 0.4528 | 0.4519 | 0.9040 | |
| | No log | 9.0 | 450 | 0.3318 | 0.4576 | 0.4778 | 0.4675 | 0.8997 | |
| | 0.4025 | 10.0 | 500 | 0.3198 | 0.5278 | 0.5299 | 0.5288 | 0.9049 | |
| | 0.4025 | 11.0 | 550 | 0.3157 | 0.4297 | 0.6358 | 0.5128 | 0.8909 | |
| | 0.4025 | 12.0 | 600 | 0.3024 | 0.5548 | 0.5954 | 0.5743 | 0.9188 | |
| | 0.4025 | 13.0 | 650 | 0.3670 | 0.6091 | 0.6185 | 0.6138 | 0.9149 | |
| | 0.4025 | 14.0 | 700 | 0.4036 | 0.5088 | 0.6127 | 0.5559 | 0.8998 | |
| | 0.4025 | 15.0 | 750 | 0.4116 | 0.5542 | 0.6012 | 0.5767 | 0.9085 | |
| | 0.4025 | 16.0 | 800 | 0.3971 | 0.5301 | 0.6455 | 0.5821 | 0.9095 | |
| | 0.4025 | 17.0 | 850 | 0.4887 | 0.5535 | 0.5183 | 0.5353 | 0.8977 | |
| | 0.4025 | 18.0 | 900 | 0.4385 | 0.5563 | 0.6474 | 0.5984 | 0.9106 | |
| | 0.4025 | 19.0 | 950 | 0.4007 | 0.6316 | 0.6012 | 0.6160 | 0.9219 | |
| | 0.0841 | 20.0 | 1000 | 0.3720 | 0.5709 | 0.5896 | 0.5801 | 0.9165 | |
| | 0.0841 | 21.0 | 1050 | 0.5100 | 0.6393 | 0.6012 | 0.6197 | 0.9150 | |
| | 0.0841 | 22.0 | 1100 | 0.5028 | 0.5319 | 0.6590 | 0.5886 | 0.8972 | |
| | 0.0841 | 23.0 | 1150 | 0.4347 | 0.5656 | 0.5896 | 0.5774 | 0.9149 | |
| | 0.0841 | 24.0 | 1200 | 0.4721 | 0.5861 | 0.6031 | 0.5945 | 0.9122 | |
| | 0.0841 | 25.0 | 1250 | 0.5677 | 0.6457 | 0.5549 | 0.5969 | 0.9116 | |
| | 0.0841 | 26.0 | 1300 | 0.4095 | 0.6278 | 0.6435 | 0.6356 | 0.9189 | |
| | 0.0841 | 27.0 | 1350 | 0.4633 | 0.5088 | 0.6686 | 0.5779 | 0.8989 | |
| | 0.0841 | 28.0 | 1400 | 0.3649 | 0.5617 | 0.6493 | 0.6023 | 0.9105 | |
| | 0.0841 | 29.0 | 1450 | 0.4653 | 0.5633 | 0.6262 | 0.5931 | 0.9111 | |
| | 0.0464 | 30.0 | 1500 | 0.5159 | 0.5581 | 0.6474 | 0.5995 | 0.9119 | |
| | 0.0464 | 31.0 | 1550 | 0.4562 | 0.5248 | 0.6513 | 0.5813 | 0.9090 | |
| | 0.0464 | 32.0 | 1600 | 0.4424 | 0.5665 | 0.5742 | 0.5703 | 0.9173 | |
| | 0.0464 | 33.0 | 1650 | 0.4866 | 0.5617 | 0.5703 | 0.5660 | 0.9164 | |
| | 0.0464 | 34.0 | 1700 | 0.4313 | 0.3760 | 0.4586 | 0.4132 | 0.8986 | |
| | 0.0464 | 35.0 | 1750 | 0.3786 | 0.5218 | 0.5761 | 0.5476 | 0.9093 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.1 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
| |
