metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlnet-large-cased-detect-dep
results: []
xlnet-large-cased-detect-dep
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: 0.6641
- Accuracy: 0.724
- F1: 0.7956
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.623 | 1.0 | 1502 | 0.5540 | 0.744 | 0.8184 |
| 0.6003 | 2.0 | 3004 | 0.5512 | 0.737 | 0.8084 |
| 0.5501 | 3.0 | 4506 | 0.6641 | 0.724 | 0.7956 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3