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clip-homer
bilbo991/clip-homer
clip-homer is a feature extraction model from bilbo991. 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
- Aug 2, 2023
- Updated
- Aug 3, 2023
- SHA
- 59e66171
Base models
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-homer
This model is a fine-tuned version of clip-homer on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4658
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.1
- Tokenizers 0.13.3
- Task
- Feature Extraction
- Library
- transformers
- Type
- vision-text-dual-encoder
- Created
- Aug 2, 2023
- Updated
- Aug 3, 2023