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

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: 0.7086

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
1.0749	0.6957	2	1.0893
1.0585	1.7391	5	1.0147
0.935	2.7826	8	0.8862
0.8267	3.8261	11	0.8299
0.7982	4.8696	14	0.7848
0.7295	5.9130	17	0.7512
0.7036	6.9565	20	0.7342
0.6598	8.0	23	0.7226
0.6493	8.6957	25	0.7157
0.5819	9.7391	28	0.7086
0.5695	10.7826	31	0.7087
0.5157	11.8261	34	0.7257
0.4755	12.8696	37	0.7442
0.4184	13.9130	40	0.7554
0.3399	14.9565	43	0.8076
0.2958	16.0	46	0.8420
0.2339	16.6957	48	0.9179

Framework versions

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