metadata
license: mit
base_model: xlnet-large-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlnet-large-cased-detect-dep-v5
results: []
xlnet-large-cased-detect-dep-v5
This model is a fine-tuned version of xlnet-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5925
- Accuracy: 0.73
- F1: 0.7991
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6442 | 1.0 | 751 | 0.5586 | 0.733 | 0.8150 |
| 0.6032 | 2.0 | 1502 | 0.5649 | 0.743 | 0.8163 |
| 0.5574 | 3.0 | 2253 | 0.5397 | 0.754 | 0.8148 |
| 0.5368 | 4.0 | 3004 | 0.6118 | 0.727 | 0.8062 |
| 0.5123 | 5.0 | 3755 | 0.5925 | 0.73 | 0.7991 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3