metadata
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlnet-base-cased-tweets
results: []
xlnet-base-cased-tweets
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: 0.2693
- Accuracy: 0.9287
- F1: 0.9581
- Precision: 0.9588
- Recall: 0.9575
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2517 | 1.0 | 642 | 0.3093 | 0.8804 | 0.9341 | 0.8799 | 0.9954 |
| 0.2239 | 2.0 | 1284 | 0.2935 | 0.9217 | 0.9542 | 0.9509 | 0.9575 |
| 0.2253 | 3.0 | 1926 | 0.2859 | 0.9170 | 0.9518 | 0.9422 | 0.9616 |
| 0.1936 | 4.0 | 2568 | 0.2904 | 0.9252 | 0.9559 | 0.9607 | 0.9511 |
| 0.1813 | 5.0 | 3210 | 0.2693 | 0.9287 | 0.9581 | 0.9588 | 0.9575 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1