train_conala_123_1760637662

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

• Loss: 1.2120
• Num Input Tokens Seen: 2711176

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: 1e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 123
• 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
0.7068	2.0	952	0.8008	272080
0.5092	4.0	1904	0.6760	542656
0.6811	6.0	2856	0.6976	813216
0.5899	8.0	3808	0.7501	1084392
0.3351	10.0	4760	0.8198	1354248
0.1813	12.0	5712	0.9575	1625360
0.1878	14.0	6664	1.0561	1896704
0.2657	16.0	7616	1.1292	2168936
0.2627	18.0	8568	1.2024	2439952
0.0603	20.0	9520	1.2120	2711176

Framework versions

• PEFT 0.17.1
• Transformers 4.51.3
• Pytorch 2.9.0+cu128
• Datasets 4.0.0
• Tokenizers 0.21.4