metadata
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: trueparagraph.ai-xlnet
results: []
trueparagraph.ai-xlnet
This model is a fine-tuned version of xlnet-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.8951
- F1: 0.8984
- Precision: 0.8674
- Recall: 0.9316
- Mcc: 0.7924
- Roc Auc: 0.8952
- Pr Auc: 0.8421
- Log Loss: 1.8813
- Loss: 0.2913
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Accuracy | F1 | Precision | Recall | Mcc | Roc Auc | Pr Auc | Log Loss | Validation Loss |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.649 | 0.6297 | 500 | 0.8006 | 0.8195 | 0.7457 | 0.9095 | 0.6164 | 0.8010 | 0.7233 | 4.0119 | 0.4063 |
| 0.4104 | 1.2594 | 1000 | 0.8409 | 0.8294 | 0.8892 | 0.7772 | 0.6870 | 0.8406 | 0.8020 | 2.4398 | 0.4054 |
| 0.4101 | 1.8892 | 1500 | 0.8100 | 0.8359 | 0.7332 | 0.9722 | 0.6560 | 0.8107 | 0.7266 | 3.4982 | 0.4405 |
| 0.4046 | 2.5189 | 2000 | 0.7754 | 0.8120 | 0.6959 | 0.9747 | 0.6012 | 0.7762 | 0.6909 | 3.0282 | 0.5111 |
| 0.3992 | 3.1486 | 2500 | 0.8664 | 0.8625 | 0.8843 | 0.8418 | 0.7336 | 0.8663 | 0.8232 | 2.7164 | 0.3871 |
| 0.3691 | 3.7783 | 3000 | 0.8774 | 0.8850 | 0.8303 | 0.9475 | 0.7626 | 0.8777 | 0.8128 | 1.8936 | 0.3413 |
| 0.2581 | 4.4081 | 3500 | 0.8951 | 0.8984 | 0.8674 | 0.9316 | 0.7924 | 0.8952 | 0.8421 | 1.8813 | 0.2913 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1