---
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: rubert-tiny2-ner-drugname
  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-ner-drugname

This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0549
- Precision: 0.7232
- Recall: 0.7690
- F1: 0.7454
- Accuracy: 0.9883

## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 61   | 0.0493          | 0.6413    | 0.7468 | 0.6901 | 0.9833   |
| No log        | 2.0   | 122  | 0.0417          | 0.6406    | 0.8291 | 0.7228 | 0.9855   |
| No log        | 3.0   | 183  | 0.0387          | 0.7588    | 0.7468 | 0.7528 | 0.9879   |
| No log        | 4.0   | 244  | 0.0396          | 0.7385    | 0.7595 | 0.7488 | 0.9883   |
| No log        | 5.0   | 305  | 0.0425          | 0.6897    | 0.7595 | 0.7229 | 0.9874   |
| No log        | 6.0   | 366  | 0.0465          | 0.6991    | 0.7722 | 0.7338 | 0.9876   |
| No log        | 7.0   | 427  | 0.0487          | 0.7062    | 0.7911 | 0.7463 | 0.9877   |
| No log        | 8.0   | 488  | 0.0521          | 0.7076    | 0.7658 | 0.7356 | 0.9882   |
| 0.0306        | 9.0   | 549  | 0.0540          | 0.7262    | 0.7722 | 0.7485 | 0.9883   |
| 0.0306        | 10.0  | 610  | 0.0549          | 0.7232    | 0.7690 | 0.7454 | 0.9883   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1