---
license: cc-by-nc-sa-4.0
base_model: ufal/robeczech-base
tags:
- generated_from_trainer
datasets:
- cnec
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: CNEC_1_1_robeczech-base
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: cnec
      type: cnec
      config: default
      split: validation
      args: default
    metrics:
    - name: Precision
      type: precision
      value: 0.8579982891360137
    - name: Recall
      type: recall
      value: 0.8856512141280353
    - name: F1
      type: f1
      value: 0.8716054746904193
    - name: Accuracy
      type: accuracy
      value: 0.9511284046692607
---

<!-- 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. -->

# CNEC_1_1_robeczech-base

This model is a fine-tuned version of [ufal/robeczech-base](https://huggingface.co/ufal/robeczech-base) on the cnec dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3233
- Precision: 0.8580
- Recall: 0.8857
- F1: 0.8716
- Accuracy: 0.9511

## 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: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3724        | 3.41  | 2000  | 0.3332          | 0.7990    | 0.8230 | 0.8108 | 0.9376   |
| 0.1863        | 6.81  | 4000  | 0.2656          | 0.8515    | 0.8636 | 0.8575 | 0.9455   |
| 0.1109        | 10.22 | 6000  | 0.2575          | 0.8505    | 0.8737 | 0.8619 | 0.9493   |
| 0.068         | 13.63 | 8000  | 0.2804          | 0.8567    | 0.8790 | 0.8677 | 0.9503   |
| 0.0466        | 17.04 | 10000 | 0.2952          | 0.8573    | 0.8830 | 0.8699 | 0.9498   |
| 0.0305        | 20.44 | 12000 | 0.2992          | 0.8618    | 0.8865 | 0.8740 | 0.9520   |
| 0.0231        | 23.85 | 14000 | 0.3272          | 0.8567    | 0.8843 | 0.8703 | 0.9512   |
| 0.02          | 27.26 | 16000 | 0.3233          | 0.8580    | 0.8857 | 0.8716 | 0.9511   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0