60b0ce7dacf6b8c8b0cd5ec81de17220

This model is a fine-tuned version of Qwen/Qwen2.5-3B on the contemmcm/clickbait dataset. It achieves the following results on the evaluation set:

• Loss: 2.3305
• Data Size: 0.125
• Epoch Runtime: 48.9212
• Accuracy: 0.8858
• F1 Macro: 0.8790

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	0.6289	0	14.2985	0.9423	0.9375
No log	1	650	0.0311	0.0078	15.7500	0.9983	0.9982
No log	2	1300	0.1250	0.0156	20.1476	0.9983	0.9982
No log	3	1950	0.2660	0.0312	28.8608	0.9956	0.9953
No log	4	2600	0.2846	0.0625	34.3332	0.9946	0.9943
0.0078	5	3250	2.3305	0.125	48.9212	0.8858	0.8790

Framework versions

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