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---
base_model: alexyalunin/RuBioRoBERTa
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nerel-bio-RuBioRoBERTa-base
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. -->
# nerel-bio-RuBioRoBERTa-base
This model is a fine-tuned version of [alexyalunin/RuBioRoBERTa](https://huggingface.co/alexyalunin/RuBioRoBERTa) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5262
- Precision: 0.8251
- Recall: 0.8335
- F1: 0.8293
- Accuracy: 0.8827
## 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: 6
- eval_batch_size: 6
- seed: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 102 | 1.7932 | 0.4125 | 0.4094 | 0.4110 | 0.5484 |
| No log | 2.0 | 204 | 0.5751 | 0.7711 | 0.7635 | 0.7673 | 0.8392 |
| No log | 3.0 | 306 | 0.4426 | 0.8053 | 0.8163 | 0.8107 | 0.8727 |
| No log | 4.0 | 408 | 0.4545 | 0.8070 | 0.8049 | 0.8060 | 0.8707 |
| 0.8666 | 5.0 | 510 | 0.4854 | 0.8100 | 0.8024 | 0.8062 | 0.8693 |
| 0.8666 | 6.0 | 612 | 0.4791 | 0.8194 | 0.8210 | 0.8202 | 0.8805 |
| 0.8666 | 7.0 | 714 | 0.4975 | 0.8202 | 0.8306 | 0.8254 | 0.8816 |
| 0.8666 | 8.0 | 816 | 0.4997 | 0.8217 | 0.8304 | 0.8260 | 0.8817 |
| 0.8666 | 9.0 | 918 | 0.5237 | 0.8237 | 0.8318 | 0.8277 | 0.8821 |
| 0.0548 | 10.0 | 1020 | 0.5262 | 0.8251 | 0.8335 | 0.8293 | 0.8827 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2
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