UNER_subword_tk_en_lora_alpha_512_drop_0.3_rank_256_seed_42
This model is a fine-tuned version of xlm-roberta-base on the universalner/universal_ner en_ewt dataset. It achieves the following results on the evaluation set:
- Loss: 0.0920
- Precision: 0.802
- Recall: 0.8302
- F1: 0.8159
- Accuracy: 0.9850
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: 0.0001
- 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
- num_epochs: 20.0
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 392 | 0.0788 | 0.6623 | 0.7816 | 0.7170 | 0.9762 |
0.1163 | 2.0 | 784 | 0.0638 | 0.7512 | 0.7940 | 0.7720 | 0.9822 |
0.0451 | 3.0 | 1176 | 0.0626 | 0.7405 | 0.8240 | 0.7800 | 0.9827 |
0.0331 | 4.0 | 1568 | 0.0597 | 0.7341 | 0.8147 | 0.7723 | 0.9824 |
0.0331 | 5.0 | 1960 | 0.0617 | 0.7648 | 0.8313 | 0.7966 | 0.9845 |
0.0267 | 6.0 | 2352 | 0.0635 | 0.7725 | 0.8261 | 0.7984 | 0.9848 |
0.0215 | 7.0 | 2744 | 0.0693 | 0.7786 | 0.8302 | 0.8036 | 0.9843 |
0.0177 | 8.0 | 3136 | 0.0768 | 0.7866 | 0.8126 | 0.7994 | 0.9845 |
0.0149 | 9.0 | 3528 | 0.0675 | 0.7968 | 0.8364 | 0.8162 | 0.9851 |
0.0149 | 10.0 | 3920 | 0.0708 | 0.8100 | 0.8251 | 0.8174 | 0.9855 |
0.0131 | 11.0 | 4312 | 0.0723 | 0.7913 | 0.8282 | 0.8093 | 0.9850 |
0.0107 | 12.0 | 4704 | 0.0799 | 0.7900 | 0.8219 | 0.8057 | 0.9846 |
0.0098 | 13.0 | 5096 | 0.0834 | 0.8069 | 0.8178 | 0.8123 | 0.9845 |
0.0098 | 14.0 | 5488 | 0.0817 | 0.7960 | 0.8199 | 0.8078 | 0.9844 |
0.0082 | 15.0 | 5880 | 0.0864 | 0.8022 | 0.8230 | 0.8125 | 0.9848 |
0.0073 | 16.0 | 6272 | 0.0906 | 0.7984 | 0.8199 | 0.8090 | 0.9848 |
0.0059 | 17.0 | 6664 | 0.0899 | 0.8077 | 0.8261 | 0.8168 | 0.9850 |
0.006 | 18.0 | 7056 | 0.0914 | 0.7940 | 0.8261 | 0.8097 | 0.9851 |
0.006 | 19.0 | 7448 | 0.0914 | 0.7939 | 0.8333 | 0.8131 | 0.9847 |
0.0052 | 20.0 | 7840 | 0.0920 | 0.802 | 0.8302 | 0.8159 | 0.9850 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
Model tree for Darius07/UNER_subword_tk_en_lora_alpha_512_drop_0.3_rank_256_seed_42
Base model
FacebookAI/xlm-roberta-base
Finetuned
this model
Dataset used to train Darius07/UNER_subword_tk_en_lora_alpha_512_drop_0.3_rank_256_seed_42
Evaluation results
- Precision on universalner/universal_ner en_ewtvalidation set self-reported0.802
- Recall on universalner/universal_ner en_ewtvalidation set self-reported0.830
- F1 on universalner/universal_ner en_ewtvalidation set self-reported0.816
- Accuracy on universalner/universal_ner en_ewtvalidation set self-reported0.985