---
base_model: alexyalunin/RuBioBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nerel-bio-RuBioBERT-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-RuBioBERT-base

This model is a fine-tuned version of [alexyalunin/RuBioBERT](https://huggingface.co/alexyalunin/RuBioBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6187
- Precision: 0.8107
- Recall: 0.8157
- F1: 0.8132
- Accuracy: 0.8721

## 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: 4
- 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   | 153  | 0.8937          | 0.7363    | 0.7078 | 0.7218 | 0.7998   |
| No log        | 2.0   | 306  | 0.5753          | 0.7907    | 0.7798 | 0.7852 | 0.8527   |
| No log        | 3.0   | 459  | 0.5308          | 0.7893    | 0.7856 | 0.7875 | 0.8559   |
| 0.9025        | 4.0   | 612  | 0.5477          | 0.7956    | 0.7962 | 0.7959 | 0.8618   |
| 0.9025        | 5.0   | 765  | 0.5732          | 0.8011    | 0.8037 | 0.8024 | 0.8646   |
| 0.9025        | 6.0   | 918  | 0.5551          | 0.8085    | 0.8082 | 0.8084 | 0.8693   |
| 0.133         | 7.0   | 1071 | 0.5813          | 0.8082    | 0.8082 | 0.8082 | 0.8701   |
| 0.133         | 8.0   | 1224 | 0.6006          | 0.8053    | 0.8131 | 0.8092 | 0.8687   |
| 0.133         | 9.0   | 1377 | 0.6183          | 0.8104    | 0.8159 | 0.8131 | 0.8723   |
| 0.0406        | 10.0  | 1530 | 0.6187          | 0.8107    | 0.8157 | 0.8132 | 0.8721   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2