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_2_0_Supertypes_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: 0.8543461237274863
          - name: Recall
            type: recall
            value: 0.9012804626187526
          - name: F1
            type: f1
            value: 0.8771859296482412
          - name: Accuracy
            type: accuracy
            value: 0.9623311462755693

CNEC_2_0_Supertypes_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: 0.2853
Precision: 0.8543
Recall: 0.9013
F1: 0.8772
Accuracy: 0.9623

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.065	17.78	4000	0.1785	0.8466	0.8893	0.8674	0.9608
0.0242	35.56	8000	0.2351	0.8534	0.8922	0.8724	0.9616
0.012	53.33	12000	0.2634	0.8537	0.8988	0.8757	0.9615
0.0075	71.11	16000	0.2730	0.8606	0.9050	0.8822	0.9641
0.0049	88.89	20000	0.2853	0.8543	0.9013	0.8772	0.9623

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.0