| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | model-index: |
| | - name: xlnet-base-cased_fold_7_binary_v1 |
| | results: [] |
| | --- |
| | |
| | <!-- 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_7_binary_v1 |
| |
|
| | This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.7774 |
| | - F1: 0.8111 |
| |
|
| | ## 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 | 288 | 0.4189 | 0.7903 | |
| | | 0.432 | 2.0 | 576 | 0.3927 | 0.8045 | |
| | | 0.432 | 3.0 | 864 | 0.4868 | 0.8108 | |
| | | 0.2573 | 4.0 | 1152 | 0.6763 | 0.8019 | |
| | | 0.2573 | 5.0 | 1440 | 0.8132 | 0.8105 | |
| | | 0.1612 | 6.0 | 1728 | 0.8544 | 0.8086 | |
| | | 0.0972 | 7.0 | 2016 | 1.1274 | 0.8109 | |
| | | 0.0972 | 8.0 | 2304 | 1.2622 | 0.8056 | |
| | | 0.0515 | 9.0 | 2592 | 1.3398 | 0.8013 | |
| | | 0.0515 | 10.0 | 2880 | 1.5421 | 0.8082 | |
| | | 0.0244 | 11.0 | 3168 | 1.4931 | 0.8042 | |
| | | 0.0244 | 12.0 | 3456 | 1.5744 | 0.8045 | |
| | | 0.0287 | 13.0 | 3744 | 1.4169 | 0.8091 | |
| | | 0.0255 | 14.0 | 4032 | 1.5790 | 0.7999 | |
| | | 0.0255 | 15.0 | 4320 | 1.6094 | 0.7994 | |
| | | 0.0098 | 16.0 | 4608 | 1.5758 | 0.8006 | |
| | | 0.0098 | 17.0 | 4896 | 1.5326 | 0.8140 | |
| | | 0.0203 | 18.0 | 5184 | 1.6431 | 0.8114 | |
| | | 0.0203 | 19.0 | 5472 | 1.7105 | 0.8072 | |
| | | 0.0104 | 20.0 | 5760 | 1.6353 | 0.8139 | |
| | | 0.0062 | 21.0 | 6048 | 1.6762 | 0.8108 | |
| | | 0.0062 | 22.0 | 6336 | 1.7076 | 0.8106 | |
| | | 0.0088 | 23.0 | 6624 | 1.7887 | 0.8035 | |
| | | 0.0088 | 24.0 | 6912 | 1.7731 | 0.8099 | |
| | | 0.0026 | 25.0 | 7200 | 1.7774 | 0.8111 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.21.1 |
| | - Pytorch 1.12.0+cu113 |
| | - Datasets 2.4.0 |
| | - Tokenizers 0.12.1 |
| |
|
