train_copa_1757340178

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the copa dataset. It achieves the following results on the evaluation set:

• Loss: 0.8684
• Num Input Tokens Seen: 548544

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Input Tokens Seen
0.2414	1.0	180	0.2286	27424
0.2373	2.0	360	0.2293	54832
0.2262	3.0	540	0.2261	82256
0.2317	4.0	720	0.2303	109728
0.2219	5.0	900	0.2318	137120
0.2254	6.0	1080	0.2332	164560
0.2401	7.0	1260	0.2287	192032
0.204	8.0	1440	0.2253	219456
0.2245	9.0	1620	0.2337	246880
0.2302	10.0	1800	0.2340	274272
0.2177	11.0	1980	0.2352	301696
0.2195	12.0	2160	0.2311	329168
0.2572	13.0	2340	0.2248	356608
0.244	14.0	2520	0.2874	384096
0.1153	15.0	2700	0.3360	411552
0.142	16.0	2880	0.4949	438896
0.0976	17.0	3060	0.7797	466320
0.0193	18.0	3240	0.8170	493664
0.0312	19.0	3420	0.8626	521088
0.0107	20.0	3600	0.8684	548544

Framework versions

• PEFT 0.15.2
• Transformers 4.51.3
• Pytorch 2.8.0+cu128
• Datasets 3.6.0
• Tokenizers 0.21.1