---
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: rubert-tiny2-odonata-extended-305-1-ner
  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. -->

# rubert-tiny2-odonata-extended-305-1-ner

This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0181
- Precision: 0.7075
- Recall: 0.2799
- F1: 0.4011
- Accuracy: 0.9963

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 213  | 0.0343          | 0.0       | 0.0    | 0.0    | 0.9952   |
| No log        | 2.0   | 426  | 0.0219          | 0.0       | 0.0    | 0.0    | 0.9952   |
| 0.045         | 3.0   | 639  | 0.0151          | 0.0       | 0.0    | 0.0    | 0.9952   |
| 0.045         | 4.0   | 852  | 0.0121          | 0.7727    | 0.1269 | 0.2179 | 0.9957   |
| 0.0065        | 5.0   | 1065 | 0.0127          | 0.6296    | 0.1269 | 0.2112 | 0.9957   |
| 0.0065        | 6.0   | 1278 | 0.0116          | 0.6667    | 0.2463 | 0.3597 | 0.9962   |
| 0.0065        | 7.0   | 1491 | 0.0107          | 0.6696    | 0.2873 | 0.4021 | 0.9964   |
| 0.0047        | 8.0   | 1704 | 0.0115          | 0.7158    | 0.2537 | 0.3747 | 0.9963   |
| 0.0047        | 9.0   | 1917 | 0.0117          | 0.7327    | 0.2761 | 0.4011 | 0.9963   |
| 0.0037        | 10.0  | 2130 | 0.0115          | 0.675     | 0.3022 | 0.4175 | 0.9964   |
| 0.0037        | 11.0  | 2343 | 0.0128          | 0.6990    | 0.2687 | 0.3881 | 0.9963   |
| 0.0032        | 12.0  | 2556 | 0.0136          | 0.6931    | 0.2612 | 0.3794 | 0.9963   |
| 0.0032        | 13.0  | 2769 | 0.0136          | 0.7       | 0.2873 | 0.4074 | 0.9963   |
| 0.0032        | 14.0  | 2982 | 0.0132          | 0.6774    | 0.3134 | 0.4286 | 0.9964   |
| 0.0026        | 15.0  | 3195 | 0.0137          | 0.6942    | 0.3134 | 0.4319 | 0.9963   |
| 0.0026        | 16.0  | 3408 | 0.0140          | 0.7193    | 0.3060 | 0.4293 | 0.9964   |
| 0.0022        | 17.0  | 3621 | 0.0144          | 0.6991    | 0.2948 | 0.4147 | 0.9964   |
| 0.0022        | 18.0  | 3834 | 0.0157          | 0.7156    | 0.2910 | 0.4138 | 0.9964   |
| 0.0019        | 19.0  | 4047 | 0.0166          | 0.6923    | 0.2351 | 0.3510 | 0.9962   |
| 0.0019        | 20.0  | 4260 | 0.0163          | 0.72      | 0.2687 | 0.3913 | 0.9963   |
| 0.0019        | 21.0  | 4473 | 0.0159          | 0.6957    | 0.2985 | 0.4178 | 0.9963   |
| 0.0017        | 22.0  | 4686 | 0.0165          | 0.6696    | 0.2873 | 0.4021 | 0.9962   |
| 0.0017        | 23.0  | 4899 | 0.0174          | 0.6952    | 0.2724 | 0.3914 | 0.9963   |
| 0.0015        | 24.0  | 5112 | 0.0180          | 0.6882    | 0.2388 | 0.3546 | 0.9961   |
| 0.0015        | 25.0  | 5325 | 0.0184          | 0.6915    | 0.2425 | 0.3591 | 0.9962   |
| 0.0014        | 26.0  | 5538 | 0.0183          | 0.7041    | 0.2575 | 0.3770 | 0.9962   |
| 0.0014        | 27.0  | 5751 | 0.0177          | 0.7009    | 0.2799 | 0.4000 | 0.9963   |
| 0.0014        | 28.0  | 5964 | 0.0180          | 0.7075    | 0.2799 | 0.4011 | 0.9963   |
| 0.0013        | 29.0  | 6177 | 0.0178          | 0.6991    | 0.2948 | 0.4147 | 0.9963   |
| 0.0013        | 30.0  | 6390 | 0.0181          | 0.7075    | 0.2799 | 0.4011 | 0.9963   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cpu
- Datasets 2.19.2
- Tokenizers 0.19.1