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gajanhcc/
finetune_colpali_v1_2-ownep6

Name: finetune_colpali_v1_2-ownep6
Availability: InStock

transformers

safetensors

colpali

generated_from_trainer

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

finetune

gemma

endpoints_compatible

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finetune_colpali_v1_2-ownep6

This model is a fine-tuned version of vidore/colpaligemma-3b-pt-448-base on the gajanhcc/fashion-query-dataset-10samples dataset. It achieves the following results on the evaluation set:

Loss: 0.0020

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 OptimizerNames.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: 6

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.01	1	0.2341
0.0068	1.0	100	0.0022
0.0	2.0	200	0.0038
0.0	3.0	300	0.0036
0.0001	4.0	400	0.0008
0.0018	5.0	500	0.0015
0.0002	6.0	600	0.0020

Framework versions

Transformers 4.47.1
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1

gajanhcc/finetune_colpali_v1_2-ownep6

finetune_colpali_v1_2-ownep6

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gajanhcc/
finetune_colpali_v1_2-ownep6