metadata

library_name: transformers
license: cc-by-4.0
base_model: Goader/liberta-large
tags:
  - generated_from_trainer
datasets:
  - universal_dependencies
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: liberta-large-upos
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: universal_dependencies
          type: universal_dependencies
          config: uk_iu
          split: validation
          args: uk_iu
        metrics:
          - name: Precision
            type: precision
            value: 0.8100632457506624
          - name: Recall
            type: recall
            value: 0.7466487546768732
          - name: F1
            type: f1
            value: 0.7541998712736135
          - name: Accuracy
            type: accuracy
            value: 0.8675486133248327

liberta-large-upos

This model is a fine-tuned version of Goader/liberta-large on the universal_dependencies dataset. It achieves the following results on the evaluation set:

Loss: 0.3346
Precision: 0.8101
Recall: 0.7466
F1: 0.7542
Accuracy: 0.8675

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: 5e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	338	1.0412	0.5939	0.4306	0.4617	0.5790
No log	2.0	676	0.6850	0.6114	0.5788	0.5745	0.7115
No log	3.0	1014	0.6075	0.6787	0.6205	0.6241	0.7389
No log	4.0	1352	0.5585	0.7178	0.6393	0.6425	0.7608
No log	5.0	1690	0.4762	0.7424	0.6737	0.6874	0.7984
No log	6.0	2028	0.4203	0.7159	0.6962	0.6946	0.8228
No log	7.0	2366	0.4275	0.7403	0.7081	0.7028	0.8205
No log	8.0	2704	0.3789	0.7909	0.7189	0.7282	0.8470
No log	9.0	3042	0.3431	0.8051	0.7415	0.7484	0.8626
No log	10.0	3380	0.3346	0.8101	0.7466	0.7542	0.8675

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1