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

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: 0.0365
- Precision: 0.7055
- Recall: 0.7658
- F1: 0.7344
- Accuracy: 0.9885

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 61   | 0.0524          | 0.7588    | 0.5475 | 0.6360 | 0.9850   |
| No log        | 2.0   | 122  | 0.0485          | 0.56      | 0.7975 | 0.6580 | 0.9825   |
| No log        | 3.0   | 183  | 0.0361          | 0.7029    | 0.7563 | 0.7287 | 0.9884   |
| No log        | 4.0   | 244  | 0.0368          | 0.7591    | 0.7278 | 0.7431 | 0.9894   |
| No log        | 5.0   | 305  | 0.0365          | 0.7055    | 0.7658 | 0.7344 | 0.9885   |


### Framework versions

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