---
base_model: DeepPavlov/rubert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nerel-bio-rubert-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-rubert-base

This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6122
- Precision: 0.7873
- Recall: 0.7882
- F1: 0.7878
- Accuracy: 0.8601

## 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  | 1.1211          | 0.6196    | 0.5809 | 0.5996 | 0.7125   |
| No log        | 2.0   | 204  | 0.6800          | 0.7333    | 0.7165 | 0.7248 | 0.8137   |
| No log        | 3.0   | 306  | 0.5985          | 0.7445    | 0.7488 | 0.7466 | 0.8303   |
| No log        | 4.0   | 408  | 0.5673          | 0.7608    | 0.7622 | 0.7615 | 0.8402   |
| 0.7954        | 5.0   | 510  | 0.5665          | 0.7751    | 0.7702 | 0.7726 | 0.8485   |
| 0.7954        | 6.0   | 612  | 0.5934          | 0.7826    | 0.7742 | 0.7784 | 0.8544   |
| 0.7954        | 7.0   | 714  | 0.5804          | 0.7795    | 0.7751 | 0.7773 | 0.8527   |
| 0.7954        | 8.0   | 816  | 0.6075          | 0.7839    | 0.7878 | 0.7858 | 0.8577   |
| 0.7954        | 9.0   | 918  | 0.6139          | 0.7887    | 0.7889 | 0.7888 | 0.8614   |
| 0.1024        | 10.0  | 1020 | 0.6122          | 0.7873    | 0.7882 | 0.7878 | 0.8601   |


### Framework versions

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