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_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

CNEC_1_1_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: 0.3233
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