This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-1, the GaetanMichelet/chat-120_ft_task-1 and the GaetanMichelet/chat-180_ft_task-1 datasets. It achieves the following results on the evaluation set:

Loss: 1.2262

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
2.0099	0.9412	8	1.9311
1.5434	2.0	17	1.5801
1.4423	2.9412	25	1.4170
1.2232	4.0	34	1.2908
1.0943	4.9412	42	1.2430
0.9751	6.0	51	1.2262
0.739	6.9412	59	1.3161
0.4877	8.0	68	1.5278
0.2813	8.9412	76	1.8161
0.1579	10.0	85	2.2197
0.0849	10.9412	93	2.5830
0.0474	12.0	102	2.6015
0.0374	12.9412	110	2.7205

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-1_180-samples_config-2

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

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

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