metadata
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-large-azsci-topics
results: []
xlm-roberta-large-azsci-topics
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4012
- Precision: 0.9115
- Recall: 0.9158
- F1: 0.9121
- Accuracy: 0.9158
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 | 0.6402 | 0.8063 | 0.8073 | 0.7900 | 0.8073 |
| 1.0792 | 2.0 | 576 | 0.4482 | 0.8827 | 0.8776 | 0.8743 | 0.8776 |
| 1.0792 | 3.0 | 864 | 0.3947 | 0.8968 | 0.9019 | 0.8977 | 0.9019 |
| 0.3135 | 4.0 | 1152 | 0.4177 | 0.9043 | 0.9080 | 0.9047 | 0.9080 |
| 0.3135 | 5.0 | 1440 | 0.4012 | 0.9115 | 0.9158 | 0.9121 | 0.9158 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2