metadata
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: edos-2023-baseline-xlm-roberta-base-label_vector
results: []
edos-2023-baseline-xlm-roberta-base-label_vector
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5797
- F1: 0.2746
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 2.1596 | 1.18 | 100 | 1.9772 | 0.0891 |
| 1.8651 | 2.35 | 200 | 1.7720 | 0.1159 |
| 1.6848 | 3.53 | 300 | 1.7193 | 0.1892 |
| 1.5532 | 4.71 | 400 | 1.6794 | 0.2191 |
| 1.466 | 5.88 | 500 | 1.6095 | 0.2419 |
| 1.3562 | 7.06 | 600 | 1.5771 | 0.2694 |
| 1.2909 | 8.24 | 700 | 1.5761 | 0.2707 |
| 1.2027 | 9.41 | 800 | 1.5747 | 0.2764 |
| 1.192 | 10.59 | 900 | 1.5893 | 0.2686 |
| 1.1256 | 11.76 | 1000 | 1.5797 | 0.2746 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2