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kotaro0918/
Japanese_colpali

Name: Japanese_colpali
Availability: InStock

transformers

safetensors

generated_from_trainer

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

finetune

gemma

endpoints_compatible

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Japanese_colpali

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

Loss: 0.3273
Model Preparation Time: 0.0061

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: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time
No log	0.0144	1	0.3660	0.0061
0.5545	1.4440	100	0.3213	0.0061
0.3	2.8881	200	0.3279	0.0061

Framework versions

Transformers 4.46.0
Pytorch 2.5.0+cu121
Datasets 3.0.2
Tokenizers 0.20.1

kotaro0918/Japanese_colpali

Japanese_colpali

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

kotaro0918/
Japanese_colpali