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, the GaetanMichelet/chat-120_ft_task-2_auto and the GaetanMichelet/chat-180_ft_task-2_auto datasets. It achieves the following results on the evaluation set:

Loss: 0.9985

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
1.4597	1.0	17	1.4484
1.2836	2.0	34	1.2670
1.0573	3.0	51	1.0740
0.9449	4.0	68	1.0341
0.9261	5.0	85	1.0129
0.8846	6.0	102	0.9985
0.8643	7.0	119	0.9999
0.7576	8.0	136	1.0171
0.6809	9.0	153	1.0483
0.6404	10.0	170	1.0951
0.5943	11.0	187	1.1375
0.4267	12.0	204	1.2362
0.446	13.0	221	1.2402

Framework versions

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

GaetanMichelet/Llama-31-8B_task-2_180-samples_config-1_full_auto

Llama-31-8B_task-2_180-samples_config-1_full_auto

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

GaetanMichelet/
Llama-31-8B_task-2_180-samples_config-1_full_auto