davanstrien HF staff commited on
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End of training

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README.md ADDED
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+ ---
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+ base_model: vidore/colpaligemma-3b-pt-448-base
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+ library_name: peft
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+ license: gemma
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: finetune_colpali_v1_2-ufo-4bit
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+ results: []
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+ ---
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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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+
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+ # finetune_colpali_v1_2-ufo-4bit
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+
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7493
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+ - Model Preparation Time: 0.0063
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 50
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+ - training_steps: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
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+ |:-------------:|:------:|:----:|:---------------:|:----------------------:|
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+ | No log | 0.0041 | 1 | 0.7471 | 0.0063 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.0
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+ - Tokenizers 0.19.1
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+ "loftq_config": {},
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+ "lora_alpha": 32,
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+ "lora_dropout": 0.1,
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+ "megatron_config": null,
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+ "megatron_core": "megatron.core",
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+ "peft_type": "LORA",
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+ "r": 32,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": "(.*(language_model).*(down_proj|gate_proj|up_proj|k_proj|q_proj|v_proj|o_proj).*$|.*(custom_text_proj).*$)",
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+ "task_type": "FEATURE_EXTRACTION",
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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