metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-base-finetuned-pos
results: []
xlm-roberta-base-finetuned-pos
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4040
- Precision: 0.8842
- Recall: 0.9000
- F1: 0.8920
- Accuracy: 0.8868
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 457 | 0.3673 | 0.8785 | 0.8932 | 0.8858 | 0.8903 |
| 0.6886 | 2.0 | 914 | 0.4011 | 0.8817 | 0.9001 | 0.8908 | 0.8858 |
| 0.2513 | 3.0 | 1371 | 0.4040 | 0.8842 | 0.9000 | 0.8920 | 0.8868 |
Framework versions
- Transformers 4.27.1
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2