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 and the GaetanMichelet/chat-120_ft_task-3_auto datasets. It achieves the following results on the evaluation set:

Loss: 0.3260

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
2.0265	1.0	11	1.8663
0.6418	2.0	22	0.6536
0.2518	3.0	33	0.4136
0.3244	4.0	44	0.3523
0.3276	5.0	55	0.3385
0.3029	6.0	66	0.3260
0.2127	7.0	77	0.3446
0.1592	8.0	88	0.3747
0.1194	9.0	99	0.4065
0.0429	10.0	110	0.4991
0.0213	11.0	121	0.5293
0.0509	12.0	132	0.5701
0.0154	13.0	143	0.5772

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-3_120-samples_config-1_auto

Llama-31-8B_task-3_120-samples_config-1_auto

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

GaetanMichelet/
Llama-31-8B_task-3_120-samples_config-1_auto