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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: 0.8579982891360137
- 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
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