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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_2-german_ver2-4bit |
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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_2-german_ver2-4bit |
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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 German_docx dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0559 |
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- Model Preparation Time: 0.0099 |
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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 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: 10 |
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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 | 0.0816 | 1 | 0.3744 | 0.0099 | |
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| 1.6073 | 0.8163 | 10 | 0.3027 | 0.0099 | |
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| 1.2318 | 1.6327 | 20 | 0.2157 | 0.0099 | |
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| 0.6498 | 2.4490 | 30 | 0.1428 | 0.0099 | |
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| 0.5073 | 3.2653 | 40 | 0.1181 | 0.0099 | |
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| 0.5106 | 4.0816 | 50 | 0.1069 | 0.0099 | |
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| 0.2965 | 4.8980 | 60 | 0.0969 | 0.0099 | |
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| 0.3175 | 5.7143 | 70 | 0.0922 | 0.0099 | |
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| 0.1775 | 6.5306 | 80 | 0.1089 | 0.0099 | |
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| 0.1966 | 7.3469 | 90 | 0.0649 | 0.0099 | |
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| 0.1317 | 8.1633 | 100 | 0.0477 | 0.0099 | |
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| 0.1287 | 8.9796 | 110 | 0.0503 | 0.0099 | |
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| 0.2576 | 9.7959 | 120 | 0.0559 | 0.0099 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.3.1 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.1 |
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