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weathon
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smiles_llava

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blip
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End of training

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  1. README.md +60 -0
  2. config.json +29 -0
  3. generation_config.json +7 -0
  4. model.safetensors +3 -0
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: bsd-3-clause
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+ base_model: Salesforce/blip-image-captioning-base
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: smiles_llava
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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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+ # smiles_llava
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+
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+ This model is a fine-tuned version of [Salesforce/blip-image-captioning-base](https://huggingface.co/Salesforce/blip-image-captioning-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - eval_loss: 0.0174
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+ - eval_accuracy: 0.8140
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+ - eval_runtime: 2.6673
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+ - eval_samples_per_second: 64.486
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+ - eval_steps_per_second: 2.249
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+ - epoch: 2.2621
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+ - step: 10100
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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: 3e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 64
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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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+ - num_epochs: 5
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+ - mixed_precision_training: Native AMP
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.2
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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+ {
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+ "_name_or_path": "Salesforce/blip-image-captioning-base",
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+ "architectures": [
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+ "BlipForConditionalGeneration"
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+ ],
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+ "image_text_hidden_size": 256,
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+ "initializer_factor": 1.0,
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+ "initializer_range": 0.02,
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+ "label_smoothing": 0.0,
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+ "logit_scale_init_value": 2.6592,
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+ "model_type": "blip",
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+ "projection_dim": 512,
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+ "text_config": {
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+ "_attn_implementation_autoset": true,
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+ "initializer_factor": 1.0,
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+ "model_type": "blip_text_model",
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+ "num_attention_heads": 12
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+ },
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.48.2",
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+ "vision_config": {
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+ "_attn_implementation_autoset": true,
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+ "dropout": 0.0,
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+ "initializer_factor": 1.0,
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+ "initializer_range": 0.02,
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+ "model_type": "blip_vision_model",
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+ "num_channels": 3
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+ }
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+ }
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