
<!-- 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-test

This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on the arampacha/rsicd dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2656

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "datasets": ["arampacha/rsicd"], "model-index": [{"name": "clip-test", "results": []}]}
transformers pytorch tensorboard clip zero-shot-image-classification generated_from_trainer dataset:arampacha/rsicd endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #clip #zero-shot-image-classification #generated_from_trainer #dataset-arampacha/rsicd #endpoints_compatible #region-us 




# clip-test

This model is a fine-tuned version of openai/clip-vit-base-patch32 on the arampacha/rsicd dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2656

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6

# clip-test

This model is a fine-tuned version of openai/clip-vit-base-patch32 on the arampacha/rsicd dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2656 ## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #clip #zero-shot-image-classification #generated_from_trainer #dataset-arampacha/rsicd #endpoints_compatible #region-us 
 # clip-test

This model is a fine-tuned version of openai/clip-vit-base-patch32 on the arampacha/rsicd dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2656 ## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #clip #zero-shot-image-classification #generated_from_trainer #dataset-arampacha/rsicd #endpoints_compatible #region-us 
# clip-test

This model is a fine-tuned version of openai/clip-vit-base-patch32 on the arampacha/rsicd dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2656## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0### Training results### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6