<!-- 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_3_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: 1.8649
- F1: 0.8044
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 | 289 | 0.4483 | 0.8000 |
| 0.4228 | 2.0 | 578 | 0.4264 | 0.8040 |
| 0.4228 | 3.0 | 867 | 0.5341 | 0.8056 |
| 0.2409 | 4.0 | 1156 | 0.9077 | 0.8103 |
| 0.2409 | 5.0 | 1445 | 1.1069 | 0.7889 |
| 0.1386 | 6.0 | 1734 | 1.0288 | 0.8093 |
| 0.0817 | 7.0 | 2023 | 1.2477 | 0.8049 |
| 0.0817 | 8.0 | 2312 | 1.5915 | 0.7872 |
| 0.0465 | 9.0 | 2601 | 1.5323 | 0.8035 |
| 0.0465 | 10.0 | 2890 | 1.4351 | 0.7989 |
| 0.0376 | 11.0 | 3179 | 1.4639 | 0.7916 |
| 0.0376 | 12.0 | 3468 | 1.6027 | 0.7956 |
| 0.0234 | 13.0 | 3757 | 1.7860 | 0.7931 |
| 0.0109 | 14.0 | 4046 | 1.8567 | 0.7934 |
| 0.0109 | 15.0 | 4335 | 1.8294 | 0.8053 |
| 0.0115 | 16.0 | 4624 | 1.7799 | 0.7971 |
| 0.0115 | 17.0 | 4913 | 1.5935 | 0.8000 |
| 0.0142 | 18.0 | 5202 | 1.8136 | 0.8066 |
| 0.0142 | 19.0 | 5491 | 1.7718 | 0.8063 |
| 0.0124 | 20.0 | 5780 | 1.8581 | 0.8053 |
| 0.0083 | 21.0 | 6069 | 1.8523 | 0.8056 |
| 0.0083 | 22.0 | 6358 | 1.8408 | 0.8035 |
| 0.0045 | 23.0 | 6647 | 1.8347 | 0.8040 |
| 0.0045 | 24.0 | 6936 | 1.8683 | 0.8067 |
| 0.0005 | 25.0 | 7225 | 1.8649 | 0.8044 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
