---
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: 0.8354960234407702
    - name: Recall
      type: recall
      value: 0.8812362030905078
    - name: F1
      type: f1
      value: 0.8577567683712936
    - name: Accuracy
      type: accuracy
      value: 0.9450064850843061
---

<!-- 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: 0.2816
- Precision: 0.8355
- Recall: 0.8812
- F1: 0.8578
- Accuracy: 0.9450

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7852        | 10.2  | 1500  | 0.6287          | 0.3577    | 0.2375 | 0.2855 | 0.8413   |
| 0.3806        | 20.41 | 3000  | 0.3455          | 0.7275    | 0.7779 | 0.7519 | 0.9240   |
| 0.2384        | 30.61 | 4500  | 0.2764          | 0.8139    | 0.8552 | 0.8340 | 0.9383   |
| 0.1722        | 40.82 | 6000  | 0.2640          | 0.8361    | 0.8693 | 0.8524 | 0.9450   |
| 0.1357        | 51.02 | 7500  | 0.2666          | 0.8362    | 0.8702 | 0.8529 | 0.9454   |
| 0.1115        | 61.22 | 9000  | 0.2697          | 0.8423    | 0.8751 | 0.8584 | 0.9457   |
| 0.098         | 71.43 | 10500 | 0.2816          | 0.8355    | 0.8812 | 0.8578 | 0.9450   |


### Framework versions

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