README.md

metadata

license: mit
base_model: xlnet-base-cased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: baseline_xlnet-base-cased_epoch2_batch2_lr2e-05_w0.01
    results: []

baseline_xlnet-base-cased_epoch2_batch2_lr2e-05_w0.01

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: 0.5189
• Accuracy: 0.8854
• F1: 0.8442
• Precision: 0.8558
• Recall: 0.8328

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.7846	1.0	1575	0.6591	0.8343	0.7453	0.872	0.6507
0.536	2.0	3150	0.5189	0.8854	0.8442	0.8558	0.8328

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.2
• Tokenizers 0.13.3