<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
xlnet-base-cased_fold_6_binary_v1
This model is a fine-tuned version of xlnet-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6214
- F1: 0.8352
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: 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: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 290 | 0.4174 | 0.7980 |
| 0.4661 | 2.0 | 580 | 0.4118 | 0.8142 |
| 0.4661 | 3.0 | 870 | 0.5152 | 0.8331 |
| 0.2714 | 4.0 | 1160 | 0.6901 | 0.8242 |
| 0.2714 | 5.0 | 1450 | 0.6853 | 0.8451 |
| 0.1542 | 6.0 | 1740 | 0.8570 | 0.8399 |
| 0.0935 | 7.0 | 2030 | 1.1342 | 0.8401 |
| 0.0935 | 8.0 | 2320 | 1.1763 | 0.8397 |
| 0.037 | 9.0 | 2610 | 1.3530 | 0.8215 |
| 0.037 | 10.0 | 2900 | 1.3826 | 0.8402 |
| 0.0351 | 11.0 | 3190 | 1.4057 | 0.8374 |
| 0.0351 | 12.0 | 3480 | 1.4259 | 0.8455 |
| 0.0159 | 13.0 | 3770 | 1.4270 | 0.8431 |
| 0.0249 | 14.0 | 4060 | 1.4215 | 0.8442 |
| 0.0249 | 15.0 | 4350 | 1.4245 | 0.8408 |
| 0.0197 | 16.0 | 4640 | 1.4171 | 0.8353 |
| 0.0197 | 17.0 | 4930 | 1.4537 | 0.8383 |
| 0.0137 | 18.0 | 5220 | 1.4786 | 0.8430 |
| 0.0068 | 19.0 | 5510 | 1.5635 | 0.8443 |
| 0.0068 | 20.0 | 5800 | 1.5527 | 0.8378 |
| 0.0062 | 21.0 | 6090 | 1.5917 | 0.8460 |
| 0.0062 | 22.0 | 6380 | 1.6317 | 0.8318 |
| 0.005 | 23.0 | 6670 | 1.6226 | 0.8340 |
| 0.005 | 24.0 | 6960 | 1.6378 | 0.8310 |
| 0.007 | 25.0 | 7250 | 1.6214 | 0.8352 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
