This model is a fine-tuned version of google/gemma-2-2b-it on the GaetanMichelet/chat-60_ft_task-3_auto, the GaetanMichelet/chat-120_ft_task-3_auto and the GaetanMichelet/chat-180_ft_task-3_auto datasets. It achieves the following results on the evaluation set:

Loss: 0.3731

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
3.1214	0.9412	8	2.8617
1.4487	2.0	17	1.1770
0.6083	2.9412	25	0.5479
0.3481	4.0	34	0.4357
0.3365	4.9412	42	0.3944
0.3762	6.0	51	0.3785
0.2475	6.9412	59	0.3731
0.2295	8.0	68	0.3856
0.1897	8.9412	76	0.4363
0.1273	10.0	85	0.5127
0.1212	10.9412	93	0.5698
0.031	12.0	102	0.7057
0.0283	12.9412	110	0.7808
0.0227	14.0	119	0.8176

Framework versions

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

GaetanMichelet/Gemma-2-2B_task-3_180-samples_config-2_auto

Gemma-2-2B_task-3_180-samples_config-2_auto

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

GaetanMichelet/
Gemma-2-2B_task-3_180-samples_config-2_auto