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--- |
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library_name: transformers |
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license: gemma |
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base_model: vidore/colpaligemma-3b-pt-448-base |
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tags: |
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- colpali |
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- generated_from_trainer |
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model-index: |
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- name: finetune_colpali-v1_3-4bit_v2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# finetune_colpali-v1_3-4bit_v2 |
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This model is a fine-tuned version of [vidore/colpaligemma-3b-pt-448-base](https://huggingface.co/vidore/colpaligemma-3b-pt-448-base) on the RowekBrah/ColPali_ann_rep_v2_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0670 |
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- Model Preparation Time: 0.0056 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 1.5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | |
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|:-------------:|:------:|:----:|:---------------:|:----------------------:| |
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| No log | 0.0012 | 1 | 0.2103 | 0.0056 | |
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| 0.4896 | 0.1238 | 100 | 0.1170 | 0.0056 | |
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| 0.5575 | 0.2476 | 200 | 0.0940 | 0.0056 | |
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| 0.3973 | 0.3714 | 300 | 0.0920 | 0.0056 | |
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| 0.4478 | 0.4952 | 400 | 0.0836 | 0.0056 | |
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| 0.2364 | 0.6190 | 500 | 0.0808 | 0.0056 | |
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| 0.2158 | 0.7428 | 600 | 0.0742 | 0.0056 | |
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| 0.339 | 0.8666 | 700 | 0.0700 | 0.0056 | |
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| 0.2052 | 0.9904 | 800 | 0.0704 | 0.0056 | |
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| 0.1546 | 1.1151 | 900 | 0.0672 | 0.0056 | |
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| 0.2003 | 1.2389 | 1000 | 0.0672 | 0.0056 | |
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| 0.1242 | 1.3627 | 1100 | 0.0676 | 0.0056 | |
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| 0.283 | 1.4865 | 1200 | 0.0674 | 0.0056 | |
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### Framework versions |
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- Transformers 4.50.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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