toxigen-albert-binary-clsf

This model is a fine-tuned version of albert/albert-base-v1 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0000
• Precision: 1.0000
• Recall: 1.0000
• Accuracy: 1.0000

Model description

More information needed

Intended uses & limitations

Finetuning albert/albert-base-v1 on the toxigen/toxigen-data dataset on the task of binary classfication.

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: 64
• eval_batch_size: 64
• 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	Precision	Recall	Accuracy
0.0	1.0	3137	0.0000	1.0000	1.0000	1.0000
0.0001	2.0	6274	0.0000	1.0000	1.0000	1.0000

Framework versions

• Transformers 4.42.3
• Pytorch 2.1.2
• Datasets 2.20.0
• Tokenizers 0.19.1