metadata

license: mit
base_model: xlnet-base-cased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: task1_xlnet-base-cased_3_4_2e-05_0.01
    results: []

task1_xlnet-base-cased_3_4_2e-05_0.01

This model is a fine-tuned version of xlnet-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3630
Accuracy: 0.9447
F1: 0.8571
Precision: 0.8219
Recall: 0.8955

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: 2e-05
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	Precision	Recall
0.3153	1.0	1629	0.2537	0.9336	0.8356	0.7722	0.9104
0.1964	2.0	3258	0.3178	0.9392	0.8413	0.8140	0.8706
0.0756	3.0	4887	0.3630	0.9447	0.8571	0.8219	0.8955

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.3
Tokenizers 0.13.3