metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-base-ner-silvanus
results: []
xlm-roberta-base-ner-silvanus
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: 0.1169
- Precision: 0.9439
- Recall: 0.9533
- F1: 0.9486
- Accuracy: 0.9793
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: 4
- eval_batch_size: 8
- 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 |
---|---|---|---|---|---|---|---|
0.1311 | 1.0 | 9363 | 0.1125 | 0.9264 | 0.9375 | 0.9319 | 0.9736 |
0.0792 | 2.0 | 18726 | 0.1118 | 0.9402 | 0.9475 | 0.9438 | 0.9775 |
0.0393 | 3.0 | 28089 | 0.1169 | 0.9439 | 0.9533 | 0.9486 | 0.9793 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1