|
--- |
|
license: mit |
|
base_model: xlnet-base-cased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- precision |
|
- recall |
|
model-index: |
|
- name: xlnet-base-cased-HU-comple |
|
results: [] |
|
pipeline_tag: text-classification |
|
--- |
|
|
|
<!-- 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-HU-comple |
|
|
|
This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9240 |
|
- Accuracy: 0.8050 |
|
- F1: 0.7619 |
|
- Precision: 0.7568 |
|
- Recall: 0.7671 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
|
| 0.6952 | 1.0 | 90 | 0.6760 | 0.5933 | 0.0 | 0.0 | 0.0 | |
|
| 0.694 | 2.0 | 180 | 0.6782 | 0.5933 | 0.0 | 0.0 | 0.0 | |
|
| 0.6856 | 3.0 | 270 | 0.6781 | 0.5933 | 0.0 | 0.0 | 0.0 | |
|
| 0.6868 | 4.0 | 360 | 0.7132 | 0.5933 | 0.0 | 0.0 | 0.0 | |
|
| 0.6353 | 5.0 | 450 | 0.6486 | 0.6657 | 0.6685 | 0.5602 | 0.8288 | |
|
| 0.5003 | 6.0 | 540 | 0.5151 | 0.7799 | 0.7189 | 0.7481 | 0.6918 | |
|
| 0.3585 | 7.0 | 630 | 0.5237 | 0.7660 | 0.7290 | 0.6890 | 0.7740 | |
|
| 0.2167 | 8.0 | 720 | 0.7817 | 0.7883 | 0.7226 | 0.7734 | 0.6781 | |
|
| 0.1643 | 9.0 | 810 | 0.8763 | 0.7939 | 0.7597 | 0.7222 | 0.8014 | |
|
| 0.135 | 10.0 | 900 | 0.9240 | 0.8050 | 0.7619 | 0.7568 | 0.7671 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.43.0.dev0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
