---
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: 0.8457943925233645
    - name: Recall
      type: recall
      value: 0.879028697571744
    - name: F1
      type: f1
      value: 0.8620913617666162
    - name: Accuracy
      type: accuracy
      value: 0.9463553826199741
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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: 0.2802
- Precision: 0.8458
- Recall: 0.8790
- F1: 0.8621
- Accuracy: 0.9464

## 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: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7893        | 6.8   | 1000 | 0.5640          | 0.5842    | 0.4671 | 0.5191 | 0.8830   |
| 0.3629        | 13.61 | 2000 | 0.3352          | 0.7879    | 0.8035 | 0.7956 | 0.9299   |
| 0.2227        | 20.41 | 3000 | 0.2793          | 0.8264    | 0.8490 | 0.8375 | 0.9437   |
| 0.1577        | 27.21 | 4000 | 0.2646          | 0.8495    | 0.8649 | 0.8571 | 0.9477   |
| 0.1193        | 34.01 | 5000 | 0.2713          | 0.8491    | 0.8720 | 0.8604 | 0.9478   |
| 0.0947        | 40.82 | 6000 | 0.2670          | 0.8560    | 0.8742 | 0.8650 | 0.9494   |
| 0.0792        | 47.62 | 7000 | 0.2791          | 0.8551    | 0.8804 | 0.8675 | 0.9479   |
| 0.0706        | 54.42 | 8000 | 0.2802          | 0.8458    | 0.8790 | 0.8621 | 0.9464   |


### Framework versions

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