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--- |
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library_name: transformers |
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license: mit |
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base_model: vidore/colqwen2-base |
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tags: |
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- ColPali |
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- "Tambouille \U0001F372" |
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- generated_from_trainer |
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model-index: |
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- name: checkpoints |
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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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# checkpoints |
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This model is a fine-tuned version of [vidore/colqwen2-base](https://huggingface.co/vidore/colqwen2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 1.0650 |
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- eval_model_preparation_time: 0.0048 |
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- eval_runtime: 25.2744 |
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- eval_samples_per_second: 2.374 |
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- eval_steps_per_second: 0.593 |
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- step: 0 |
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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: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 1 |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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