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---
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
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