Llama-31-8B_task-2_60-samples_config-2_full

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

• Loss: 1.0628

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
1.5658	0.6957	2	1.5799
1.5614	1.7391	5	1.5293
1.4751	2.7826	8	1.4358
1.3878	3.8261	11	1.3590
1.3039	4.8696	14	1.2951
1.2412	5.9130	17	1.2337
1.1483	6.9565	20	1.1724
1.1126	8.0	23	1.1255
1.0651	8.6957	25	1.1110
1.0248	9.7391	28	1.0985
1.0323	10.7826	31	1.0890
1.0119	11.8261	34	1.0821
0.9765	12.8696	37	1.0758
0.9796	13.9130	40	1.0704
0.9428	14.9565	43	1.0683
0.9511	16.0	46	1.0637
0.9117	16.6957	48	1.0628
0.9208	17.7391	51	1.0629
0.9108	18.7826	54	1.0634
0.8903	19.8261	57	1.0640
0.8762	20.8696	60	1.0664
0.8702	21.9130	63	1.0685
0.8465	22.9565	66	1.0700
0.8409	24.0	69	1.0734

Framework versions

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