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---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlnet-base-cased_fold_8_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_8_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: 1.5333
- F1: 0.8407
## 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 | 0.3866 | 0.8172 |
| 0.4299 | 2.0 | 580 | 0.4215 | 0.8246 |
| 0.4299 | 3.0 | 870 | 0.4765 | 0.8238 |
| 0.2564 | 4.0 | 1160 | 0.7283 | 0.8350 |
| 0.2564 | 5.0 | 1450 | 0.6825 | 0.8363 |
| 0.1553 | 6.0 | 1740 | 0.9637 | 0.8339 |
| 0.0893 | 7.0 | 2030 | 1.1392 | 0.8239 |
| 0.0893 | 8.0 | 2320 | 1.1868 | 0.8231 |
| 0.0538 | 9.0 | 2610 | 1.2180 | 0.8346 |
| 0.0538 | 10.0 | 2900 | 1.2353 | 0.8253 |
| 0.0386 | 11.0 | 3190 | 1.1883 | 0.8317 |
| 0.0386 | 12.0 | 3480 | 1.2786 | 0.8375 |
| 0.0289 | 13.0 | 3770 | 1.3725 | 0.8375 |
| 0.0146 | 14.0 | 4060 | 1.3171 | 0.8463 |
| 0.0146 | 15.0 | 4350 | 1.2323 | 0.8425 |
| 0.0182 | 16.0 | 4640 | 1.3169 | 0.8485 |
| 0.0182 | 17.0 | 4930 | 1.4424 | 0.8336 |
| 0.0125 | 18.0 | 5220 | 1.4336 | 0.8385 |
| 0.0102 | 19.0 | 5510 | 1.4888 | 0.8405 |
| 0.0102 | 20.0 | 5800 | 1.5227 | 0.8419 |
| 0.0035 | 21.0 | 6090 | 1.4994 | 0.8421 |
| 0.0035 | 22.0 | 6380 | 1.4845 | 0.8424 |
| 0.0047 | 23.0 | 6670 | 1.5006 | 0.8422 |
| 0.0047 | 24.0 | 6960 | 1.5468 | 0.8422 |
| 0.0042 | 25.0 | 7250 | 1.5333 | 0.8407 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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