File size: 2,774 Bytes
2fafe07 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlnet-base-cased_fold_10_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_10_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: 1.7782
- F1: 0.8137
## 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 | 0.3796 | 0.8145 |
| 0.4196 | 2.0 | 576 | 0.4319 | 0.7810 |
| 0.4196 | 3.0 | 864 | 0.6227 | 0.8002 |
| 0.231 | 4.0 | 1152 | 0.6258 | 0.7941 |
| 0.231 | 5.0 | 1440 | 1.0692 | 0.7866 |
| 0.1307 | 6.0 | 1728 | 1.1257 | 0.8005 |
| 0.0756 | 7.0 | 2016 | 1.2283 | 0.8072 |
| 0.0756 | 8.0 | 2304 | 1.3407 | 0.8061 |
| 0.0486 | 9.0 | 2592 | 1.5232 | 0.8059 |
| 0.0486 | 10.0 | 2880 | 1.6731 | 0.8053 |
| 0.0339 | 11.0 | 3168 | 1.6536 | 0.8087 |
| 0.0339 | 12.0 | 3456 | 1.7526 | 0.7996 |
| 0.019 | 13.0 | 3744 | 1.6662 | 0.7909 |
| 0.0237 | 14.0 | 4032 | 1.6028 | 0.8071 |
| 0.0237 | 15.0 | 4320 | 1.7627 | 0.7964 |
| 0.0078 | 16.0 | 4608 | 1.6513 | 0.8169 |
| 0.0078 | 17.0 | 4896 | 1.7795 | 0.8039 |
| 0.015 | 18.0 | 5184 | 1.8669 | 0.7935 |
| 0.015 | 19.0 | 5472 | 1.6288 | 0.8118 |
| 0.0124 | 20.0 | 5760 | 1.6630 | 0.8104 |
| 0.004 | 21.0 | 6048 | 1.7418 | 0.8167 |
| 0.004 | 22.0 | 6336 | 1.7651 | 0.8128 |
| 0.0043 | 23.0 | 6624 | 1.7279 | 0.8163 |
| 0.0043 | 24.0 | 6912 | 1.8177 | 0.8093 |
| 0.004 | 25.0 | 7200 | 1.7782 | 0.8137 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
|