uner_qaf_ara
This model is a fine-tuned version of xlm-roberta-large on the uner_qaf_ara dataset. It achieves the following results on the evaluation set:
- Loss: 0.1885
- Precision: 0.7241
- Recall: 0.7206
- F1: 0.7224
- Accuracy: 0.9548
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Framework versions
- Transformers 4.31.0
- Pytorch 1.10.1+cu113
- Datasets 2.14.4
- Tokenizers 0.13.3
- Downloads last month
- 22
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for universalner/uner_qaf_ara
Base model
FacebookAI/xlm-roberta-largeEvaluation results
- Precision on uner_qaf_aravalidation set self-reported0.724
- Recall on uner_qaf_aravalidation set self-reported0.721
- F1 on uner_qaf_aravalidation set self-reported0.722
- Accuracy on uner_qaf_aravalidation set self-reported0.955