metadata
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
xlnet-base-cased-HU-comple
This model is a fine-tuned version of 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