metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-base-azsci-topics
results: []
xlm-roberta-base-azsci-topics
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5075
- Precision: 0.8624
- Recall: 0.8707
- F1: 0.8645
- Accuracy: 0.8707
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 288 | 0.8674 | 0.6762 | 0.7422 | 0.6848 | 0.7422 |
| 1.3706 | 2.0 | 576 | 0.6110 | 0.8177 | 0.8264 | 0.8104 | 0.8264 |
| 1.3706 | 3.0 | 864 | 0.5391 | 0.8407 | 0.8490 | 0.8415 | 0.8490 |
| 0.5184 | 4.0 | 1152 | 0.5059 | 0.8505 | 0.8559 | 0.8493 | 0.8559 |
| 0.5184 | 5.0 | 1440 | 0.5075 | 0.8624 | 0.8707 | 0.8645 | 0.8707 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2