---
base_model: youscan/ukr-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: gec_uk_seq2tag
  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. -->

# gec_uk_seq2tag

This model is a fine-tuned version of [youscan/ukr-roberta-base](https://huggingface.co/youscan/ukr-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2885
- Precision: 0.5978
- Recall: 0.4263
- F1: 0.4977
- Accuracy: 0.9550

## 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: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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   | 202  | 0.3200          | 0.5468    | 0.3189 | 0.4028 | 0.9493   |
| No log        | 2.0   | 405  | 0.2860          | 0.5904    | 0.3765 | 0.4598 | 0.9539   |
| 0.3194        | 3.0   | 608  | 0.2843          | 0.5733    | 0.4437 | 0.5002 | 0.9538   |
| 0.3194        | 4.0   | 811  | 0.2885          | 0.5978    | 0.4263 | 0.4977 | 0.9550   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.17.1
- Tokenizers 0.15.1