You can deploy this model and start earning money today!

svenbl80/
finetune_colpali_v1_2-german_ver2-8bit

Name: finetune_colpali_v1_2-german_ver2-8bit
Availability: InStock

transformers

safetensors

colpali

generated_from_trainer

vidore/colpaligemma-3b-pt-448-base

finetune

gemma

endpoints_compatible

Views

No views yet

finetune_colpali_v1_2-german_ver2-8bit

This model is a fine-tuned version of vidore/colpaligemma-3b-pt-448-base on the German_docx dataset. It achieves the following results on the evaluation set:

Loss: 0.1034
Model Preparation Time: 0.0101

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time
No log	0.0816	1	0.4123	0.0101
1.2101	0.8163	10	0.3859	0.0101
1.2237	1.6327	20	0.3079	0.0101
0.6883	2.4490	30	0.2464	0.0101
0.4804	3.2653	40	0.2011	0.0101
0.5187	4.0816	50	0.1792	0.0101
0.3899	4.8980	60	0.1563	0.0101
0.203	5.7143	70	0.1307	0.0101
0.1897	6.5306	80	0.0990	0.0101
0.3326	7.3469	90	0.1246	0.0101
0.3578	8.1633	100	0.1429	0.0101
0.3568	8.9796	110	0.1148	0.0101
0.1411	9.7959	120	0.1034	0.0101

Framework versions

Transformers 4.46.1
Pytorch 2.3.1
Datasets 3.1.0
Tokenizers 0.20.1

svenbl80/finetune_colpali_v1_2-german_ver2-8bit

finetune_colpali_v1_2-german_ver2-8bit

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

svenbl80/
finetune_colpali_v1_2-german_ver2-8bit