XLM_Lexical_CITA
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5541
- Accuracy: 0.78
- F1: 0.7786
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: 32
- eval_batch_size: 32
- 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
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.689 | 1.0 | 250 | 0.6043 | 0.632 | 0.5805 |
0.5712 | 2.0 | 500 | 0.5144 | 0.7335 | 0.7336 |
0.5047 | 3.0 | 750 | 0.5206 | 0.741 | 0.7402 |
0.4552 | 4.0 | 1000 | 0.4796 | 0.7785 | 0.7784 |
0.4279 | 5.0 | 1250 | 0.4892 | 0.7775 | 0.7776 |
0.391 | 6.0 | 1500 | 0.4770 | 0.78 | 0.7797 |
0.3623 | 7.0 | 1750 | 0.5276 | 0.7795 | 0.7768 |
0.341 | 8.0 | 2000 | 0.5346 | 0.779 | 0.7789 |
0.3205 | 9.0 | 2250 | 0.5315 | 0.7795 | 0.7781 |
0.3043 | 10.0 | 2500 | 0.5541 | 0.78 | 0.7786 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.21.0
- Downloads last month
- 4
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no pipeline_tag.
Model tree for phunganhsang/XLM_Lexical_CITA
Base model
FacebookAI/xlm-roberta-base