metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Final_Mixed-aug_insert_synonym-1
results: []
xlm-roberta-base-Final_Mixed-aug_insert_synonym-1
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: 1.1442
- Accuracy: 0.74
- F1: 0.7298
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: 41
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0022 | 1.0 | 88 | 0.7751 | 0.7 | 0.6764 |
| 0.7565 | 2.0 | 176 | 0.7416 | 0.67 | 0.6181 |
| 0.6017 | 3.0 | 264 | 0.6780 | 0.72 | 0.7105 |
| 0.4341 | 4.0 | 352 | 0.6895 | 0.77 | 0.7620 |
| 0.3477 | 5.0 | 440 | 0.7465 | 0.76 | 0.7535 |
| 0.2429 | 6.0 | 528 | 0.9202 | 0.73 | 0.7207 |
| 0.1659 | 7.0 | 616 | 1.1246 | 0.74 | 0.7267 |
| 0.1623 | 8.0 | 704 | 1.1442 | 0.74 | 0.7298 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3