Llama-31-8B_task-2_60-samples_config-1_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 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5999

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: 8
• total_train_batch_size: 8
• 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
0.8547	0.8696	5	0.8787
0.8316	1.9130	11	0.7978
0.7352	2.9565	17	0.7125
0.6096	4.0	23	0.6426
0.5369	4.8696	28	0.6110
0.4624	5.9130	34	0.5999
0.3577	6.9565	40	0.6314
0.3027	8.0	46	0.6916
0.2146	8.8696	51	0.7509
0.1132	9.9130	57	0.9555
0.0626	10.9565	63	1.0440
0.0376	12.0	69	1.1408
0.0262	12.8696	74	1.1577

Framework versions

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