Llama-31-8B_task-1_60-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-1_auto dataset. It achieves the following results on the evaluation set:

• Loss: 0.9200

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
1.1077	0.6957	2	1.2225
1.1089	1.7391	5	1.1334
0.954	2.7826	8	1.0066
0.9473	3.8261	11	0.9689
0.7929	4.8696	14	0.9281
0.7943	5.9130	17	0.9352
0.6696	6.9565	20	0.9296
0.5976	8.0	23	0.9200
0.5767	8.6957	25	0.9291
0.4423	9.7391	28	0.9620
0.4059	10.7826	31	1.0431
0.2734	11.8261	34	1.1927
0.2387	12.8696	37	1.3013
0.1347	13.9130	40	1.4096
0.0897	14.9565	43	1.5471

Framework versions

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