metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Final_Mixed-aug_replace_synonym-1
results: []
xlm-roberta-base-Final_Mixed-aug_replace_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: 0.8727
- Accuracy: 0.76
- F1: 0.7592
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 |
|---|---|---|---|---|---|
| 1.0219 | 1.0 | 87 | 0.7346 | 0.68 | 0.6276 |
| 0.7518 | 2.0 | 174 | 0.5934 | 0.75 | 0.7425 |
| 0.6023 | 3.0 | 261 | 0.7553 | 0.7 | 0.6975 |
| 0.479 | 4.0 | 348 | 0.7275 | 0.72 | 0.7118 |
| 0.3515 | 5.0 | 435 | 0.9068 | 0.74 | 0.7306 |
| 0.2646 | 6.0 | 522 | 0.7953 | 0.77 | 0.7633 |
| 0.2123 | 7.0 | 609 | 0.8673 | 0.77 | 0.7652 |
| 0.1535 | 8.0 | 696 | 0.8727 | 0.76 | 0.7592 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3