metadata
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlnet-base-cased-HU
results: []
xlnet-base-cased-HU
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: 0.8571
- Accuracy: 0.8465
- F1: 0.7979
- Precision: 0.875
- Recall: 0.7333
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 |
|---|---|---|---|---|---|---|---|
| 0.7086 | 1.0 | 64 | 0.6695 | 0.5866 | 0.0 | 0.0 | 0.0 |
| 0.6423 | 2.0 | 128 | 0.6102 | 0.6929 | 0.6777 | 0.5985 | 0.7810 |
| 0.5089 | 3.0 | 192 | 0.5276 | 0.7756 | 0.7016 | 0.7791 | 0.6381 |
| 0.491 | 4.0 | 256 | 0.8212 | 0.7559 | 0.6310 | 0.8413 | 0.5048 |
| 0.3367 | 5.0 | 320 | 0.6119 | 0.8189 | 0.7982 | 0.7398 | 0.8667 |
| 0.2412 | 6.0 | 384 | 0.4921 | 0.8346 | 0.7742 | 0.8889 | 0.6857 |
| 0.154 | 7.0 | 448 | 0.8891 | 0.8268 | 0.7609 | 0.8861 | 0.6667 |
| 0.1075 | 8.0 | 512 | 0.9218 | 0.8504 | 0.8021 | 0.8851 | 0.7333 |
| 0.081 | 9.0 | 576 | 0.8782 | 0.8465 | 0.7958 | 0.8837 | 0.7238 |
| 0.0727 | 10.0 | 640 | 0.8571 | 0.8465 | 0.7979 | 0.875 | 0.7333 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1