metadata

library_name: transformers
license: mit
base_model: vidore/colqwen2-base
tags:
  - ColPali
  - Tambouille 🍲
  - generated_from_trainer
model-index:
  - name: checkpoints
    results: []

checkpoints

This model is a fine-tuned version of vidore/colqwen2-base on an unknown dataset. It achieves the following results on the evaluation set:

eval_loss: 1.0650
eval_model_preparation_time: 0.0048
eval_runtime: 25.2744
eval_samples_per_second: 2.374
eval_steps_per_second: 0.593
step: 0

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: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 1

Framework versions

Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.0