Llama-31-8B_task-2_120-samples_config-2_auto

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-2_auto and the GaetanMichelet/chat-120_ft_task-2_auto datasets. It achieves the following results on the evaluation set:

• Loss: 0.5819

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
0.9245	0.9091	5	0.8871
0.8834	2.0	11	0.7984
0.7224	2.9091	16	0.7230
0.6496	4.0	22	0.6428
0.5918	4.9091	27	0.6049
0.5484	6.0	33	0.5821
0.472	6.9091	38	0.5819
0.4328	8.0	44	0.5885
0.3688	8.9091	49	0.6169
0.2923	10.0	55	0.6638
0.2063	10.9091	60	0.7679
0.1206	12.0	66	0.8585
0.0643	12.9091	71	1.0241
0.0373	14.0	77	1.0912

Framework versions

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