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Blip Image Captioning Base Test Sagemaker Tops 3

This model is a fine-tuned version of Salesforce/blip-image-captioning-base on the None dataset.

KindText modelVersionpytorch_modelBgrade

Model source

Kind
Text model
File size
944 MB
Version
vpytorch_model
Updated
Oct 6, 2026
Downloads
7
Source
Hugging Face

Source description

blip-image-captioning-base-test_sagemaker-tops-3

This model is a fine-tuned version of Salesforce/blip-image-captioning-base on the None dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-06
  • train_batch_size: 16
  • eval_batch_size: 64
  • seed: 42
  • distributed_type: sagemaker_model_parallel
  • num_devices: 2
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu117
  • Datasets 2.9.0
  • Tokenizers 0.13.2

Sources

1 source
Hugging FacePrimaryVersion 7482f97f8dacde5b85c55ee136e41a11838af6d6
huggingface.co/GHonem/blip-image-captioning-base-test_sagemaker-tops-3/tree/7482f97f8dacde5b85c55ee136e41a11838af6d6

Verified Oct 6

Model artifacts

1 artifact

pytorch_model.bin

bin · 944 MB · SHA-256 18fc3921acd8…6d72 · Hugging Face

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Source excerpts

3 excerpts

--- license: bsd-3-clause tags: - generated_from_trainer model-index: - name: blip-image-captioning-base-test_sagemaker-tops-3 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # blip-image-captioning-base-test_sagemaker-tops-3 This model is a fine-tuned version of [Salesforce/blip-image-captioning-base](https://huggingface.co/Salesforce/blip-image-captioning-base) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-06 - train_batch_size: 16 - eval_batch_size: 64 - seed: 42 - distributed_type: sagemaker_model_parallel - num_devices: 2 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - total_eval_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results ### Framework versions - Transformers 4.26.0 - Pytorch 1.13.1+cu117 - Datasets 2.9.0 - Tokenizers 0.13.2

Source context: 7 downloads · 0 likes · Pipeline image-text-to-text · Library transformers · Repo GHonem/blip-image-captioning-base-test_sagemaker-tops-3

Source context: 12 downloads · 0 likes · Pipeline image-text-to-text · Library transformers · Repo GHonem/blip-image-captioning-base-test_sagemaker-tops-3