Llama-31-8B_task-3_60-samples_config-2_full_auto

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-3_auto dataset. It achieves the following results on the evaluation set:

• Loss: 1.1526

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: 0.0001
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 16
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss
1.6601	0.6957	2	1.6697
1.6649	1.7391	5	1.6260
1.591	2.7826	8	1.5468
1.4992	3.8261	11	1.4664
1.4061	4.8696	14	1.3963
1.352	5.9130	17	1.3313
1.2367	6.9565	20	1.2646
1.2127	8.0	23	1.2216
1.1571	8.6957	25	1.2052
1.1165	9.7391	28	1.1900
1.124	10.7826	31	1.1787
1.0947	11.8261	34	1.1694
1.0606	12.8696	37	1.1634
1.0621	13.9130	40	1.1573
1.0235	14.9565	43	1.1550
1.0274	16.0	46	1.1531
0.9827	16.6957	48	1.1526
0.9959	17.7391	51	1.1536
0.9813	18.7826	54	1.1576
0.9571	19.8261	57	1.1600
0.9413	20.8696	60	1.1619
0.9355	21.9130	63	1.1652
0.9063	22.9565	66	1.1698
0.8949	24.0	69	1.1736

Framework versions

• PEFT 0.12.0
• Transformers 4.44.0
• Pytorch 2.1.2+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1