
<!-- 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

This model is a fine-tuned version of [./models/clip-roberta](https://huggingface.co/./models/clip-roberta) on the ydshieh/coco_dataset_script 2017 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7269

## 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: 256
- eval_batch_size: 256
- 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 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "datasets": ["ydshieh/coco_dataset_script"], "model-index": [{"name": "clip-roberta-finetuned", "results": []}]}
transformers pytorch tensorboard vision-text-dual-encoder feature-extraction generated_from_trainer dataset:ydshieh/coco_dataset_script endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #vision-text-dual-encoder #feature-extraction #generated_from_trainer #dataset-ydshieh/coco_dataset_script #endpoints_compatible #region-us 




# clip-roberta-finetuned

This model is a fine-tuned version of ./models/clip-roberta on the ydshieh/coco_dataset_script 2017 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7269

## 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: 256
- eval_batch_size: 256
- 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 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6

# clip-roberta-finetuned

This model is a fine-tuned version of ./models/clip-roberta on the ydshieh/coco_dataset_script 2017 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7269 ## 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: 256
- eval_batch_size: 256
- 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 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #vision-text-dual-encoder #feature-extraction #generated_from_trainer #dataset-ydshieh/coco_dataset_script #endpoints_compatible #region-us 
 # clip-roberta-finetuned

This model is a fine-tuned version of ./models/clip-roberta on the ydshieh/coco_dataset_script 2017 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7269 ## 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: 256
- eval_batch_size: 256
- 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 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #vision-text-dual-encoder #feature-extraction #generated_from_trainer #dataset-ydshieh/coco_dataset_script #endpoints_compatible #region-us 
# clip-roberta-finetuned

This model is a fine-tuned version of ./models/clip-roberta on the ydshieh/coco_dataset_script 2017 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7269## 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: 256
- eval_batch_size: 256
- 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 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6