metadata
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_ext_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: 0.8638931689779148
- name: Recall
type: recall
value: 0.8989845002672368
- name: F1
type: f1
value: 0.8810895756940808
- name: Accuracy
type: accuracy
value: 0.963311432325887
CNEC_1_1_ext_robeczech-base
This model is a fine-tuned version of ufal/robeczech-base on the cnec dataset. It achieves the following results on the evaluation set:
- Loss: 0.1985
- Precision: 0.8639
- Recall: 0.8990
- F1: 0.8811
- Accuracy: 0.9633
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: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.2585 | 6.85 | 1000 | 0.1912 | 0.8276 | 0.8696 | 0.8481 | 0.9550 |
0.1224 | 13.7 | 2000 | 0.1807 | 0.8455 | 0.8894 | 0.8669 | 0.9586 |
0.0788 | 20.55 | 3000 | 0.1715 | 0.8624 | 0.8974 | 0.8795 | 0.9643 |
0.0562 | 27.4 | 4000 | 0.1782 | 0.8650 | 0.9043 | 0.8842 | 0.9633 |
0.0432 | 34.25 | 5000 | 0.1856 | 0.8598 | 0.9017 | 0.8803 | 0.9640 |
0.0346 | 41.1 | 6000 | 0.1975 | 0.8622 | 0.8963 | 0.8789 | 0.9630 |
0.0306 | 47.95 | 7000 | 0.1985 | 0.8639 | 0.8990 | 0.8811 | 0.9633 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0