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clip-roberta-finetuned_GQA
wooseoko/clip-roberta-finetuned_GQA
clip-roberta-finetuned_GQA is a feature extraction model from wooseoko. 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 23, 2023
- Updated
- Mar 23, 2023
- SHA
- ef6c1d73
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-roberta-finetuned_GQA
This model is a fine-tuned version of ./clip-roberta on the ./GQA_script.py relation dataset. It achieves the following results on the evaluation set:
- Loss: 2.3532
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 4.26.1
- Pytorch 1.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2
- Task
- Feature Extraction
- Library
- transformers
- Type
- vision-text-dual-encoder
- Created
- Mar 23, 2023
- Updated
- Mar 23, 2023