Llama-31-8B_task-3_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-3_auto dataset. It achieves the following results on the evaluation set:

• Loss: 0.3500

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
2.1804	0.8696	5	2.1300
1.7781	1.9130	11	1.3089
0.7143	2.9565	17	0.5687
0.3741	4.0	23	0.4144
0.2554	4.8696	28	0.3896
0.2567	5.9130	34	0.3594
0.2394	6.9565	40	0.3500
0.3262	8.0	46	0.3681
0.204	8.8696	51	0.4215
0.1772	9.9130	57	0.4067
0.1163	10.9565	63	0.4379
0.062	12.0	69	0.5497
0.0248	12.8696	74	0.6054
0.0184	13.9130	80	0.6328

Framework versions

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