Llama-31-8B_task-1_120-samples_config-1

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-1 and the GaetanMichelet/chat-120_ft_task-1 datasets. It achieves the following results on the evaluation set:

• Loss: 1.2432

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
1.8587	1.0	11	1.8962
1.5582	2.0	22	1.5353
1.3116	3.0	33	1.3440
1.1103	4.0	44	1.2486
0.9015	5.0	55	1.2432
0.6339	6.0	66	1.3448
0.2953	7.0	77	1.6649
0.2611	8.0	88	1.9195
0.107	9.0	99	2.4669
0.0592	10.0	110	2.5539
0.06	11.0	121	2.4769
0.0548	12.0	132	2.9299

Framework versions

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