a037d18375a23216ded9d7f50389b96f

This model is a fine-tuned version of albert/albert-xlarge-v2 on the contemmcm/clickbait dataset. It achieves the following results on the evaluation set:

• Loss: 0.6696
• Data Size: 0.125
• Epoch Runtime: 9.5038
• Accuracy: 0.6130
• F1 Macro: 0.3801

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: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: constant
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Accuracy	F1 Macro
No log	0	0	0.9243	0	3.8836	0.3862	0.2786
No log	1	650	0.6610	0.0078	4.5910	0.6130	0.3801
No log	2	1300	0.7762	0.0156	4.7752	0.3872	0.2794
No log	3	1950	0.6736	0.0312	5.4816	0.6130	0.3801
No log	4	2600	0.6693	0.0625	6.7449	0.6130	0.3801
0.0334	5	3250	0.6696	0.125	9.5038	0.6130	0.3801

Framework versions

• Transformers 4.57.0
• Pytorch 2.8.0+cu128
• Datasets 4.3.0
• Tokenizers 0.22.1