Dagobert42/xlnet-base-cased-biored-augmented-super

This model is a fine-tuned version of xlnet-base-cased on the bigbio/biored dataset. It achieves the following results on the evaluation set:

• Loss: 0.2035
• Accuracy: 0.9315
• Precision: 0.8447
• Recall: 0.8503
• F1: 0.8469
• Weighted F1: 0.9318

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Weighted F1
No log	1.0	25	0.2497	0.9156	0.8595	0.7951	0.8242	0.9144
No log	2.0	50	0.2404	0.9215	0.843	0.838	0.8404	0.9213
No log	3.0	75	0.2595	0.9142	0.82	0.8571	0.8369	0.9161
No log	4.0	100	0.2448	0.9266	0.8539	0.8261	0.8396	0.9257

Framework versions

• Transformers 4.35.2
• Pytorch 2.0.1+cu117
• Datasets 2.12.0
• Tokenizers 0.15.0