metadata
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
datasets:
- cnec
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: CNEC2_0_Supertypes_xlm-roberta-large
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: 0.8475513428120063
- name: Recall
type: recall
value: 0.8864105741429161
- name: F1
type: f1
value: 0.8665455279628508
- name: Accuracy
type: accuracy
value: 0.9683326090105752
CNEC2_0_Supertypes_xlm-roberta-large
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the cnec dataset. It achieves the following results on the evaluation set:
- Loss: 0.1632
- Precision: 0.8476
- Recall: 0.8864
- F1: 0.8665
- Accuracy: 0.9683
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.208 | 1.0 | 7193 | 0.1642 | 0.8031 | 0.8509 | 0.8263 | 0.9620 |
| 0.149 | 2.0 | 14386 | 0.1812 | 0.8426 | 0.8781 | 0.8600 | 0.9664 |
| 0.0798 | 3.0 | 21579 | 0.1632 | 0.8476 | 0.8864 | 0.8665 | 0.9683 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0