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clip-vit-bert-coco
christti/clip-vit-bert-coco
clip-vit-bert-coco is a feature extraction model from christti. Use it when you need embeddings to search or compare text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Feature Extraction
- Library
- transformers
- Model type
- vision-text-dual-encoder
- Access
- Public
- Created
- Mar 5, 2024
- Updated
- Mar 6, 2024
- SHA
- 9dc1a4e0
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
clip-vit-bert-coco
This model was trained from scratch on the ydshieh/coco_dataset_script 2017 dataset. It achieves the following results on the evaluation set:
- eval_loss: 4.1888
- eval_runtime: 5.7658
- eval_samples_per_second: 22.2
- eval_steps_per_second: 0.173
- step: 0
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-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Feature Extraction
- Library
- transformers
- Type
- vision-text-dual-encoder
- Created
- Mar 5, 2024
- Updated
- Mar 6, 2024