metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-large-sdg-classification
results: []
datasets:
- albertmartinez/OSDG
pipeline_tag: text-classification
xlm-roberta-large-sdg-classification
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: 0.6536
- F1: 0.8114
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | F1 | Validation Loss |
|---|---|---|---|---|
| 1.7444 | 1.0 | 538 | 0.7686 | 0.8148 |
| 0.7749 | 2.0 | 1076 | 0.8000 | 0.7104 |
| 0.6165 | 3.0 | 1614 | 0.8114 | 0.6536 |
| 0.5044 | 4.0 | 2152 | 0.8140 | 0.6571 |
| 0.4217 | 5.0 | 2690 | 0.8154 | 0.6651 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.1.2.post304
- Datasets 3.2.0
- Tokenizers 0.21.0