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: 0.2094
- Accuracy: 0.9236
- F1: 0.9553
- Precision: 0.9531
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2551 | 1.0 | 642 | 0.2172 | 0.9037 | 0.9443 | 0.9311 | 0.9579 |
| 0.1981 | 2.0 | 1284 | 0.2366 | 0.9135 | 0.9500 | 0.9349 | 0.9657 |
| 0.1513 | 3.0 | 1926 | 0.2094 | 0.9236 | 0.9553 | 0.9531 | 0.9575 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1