---
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: lct-rubert-tiny2-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. -->

# lct-rubert-tiny2-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: 0.0270
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9985

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.0   | 38   | 0.1353          | 0.0       | 0.0    | 0.0 | 0.9985   |
| No log        | 2.0   | 76   | 0.0334          | 0.0       | 0.0    | 0.0 | 0.9985   |
| No log        | 3.0   | 114  | 0.0270          | 0.0       | 0.0    | 0.0 | 0.9985   |


### Framework versions

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