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# SPECTER-frozen-with-biblio-context-finetuned-review_classifier

This model is a fine-tuned version of [allenai/specter](https://huggingface.co/allenai/specter) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2606
- eval_accuracy: 0.91
- eval_f1: 0.0925
- eval_recall: 0.0490
- eval_precision: 0.8379
- eval_runtime: 1030.2818
- eval_samples_per_second: 77.649
- eval_steps_per_second: 6.471
- epoch: 1.0
- step: 6667

## 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: 4.5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 2
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["text-classification", "generated_from_trainer"], "model-index": [{"name": "SPECTER-frozen-with-biblio-context-finetuned-review_classifier", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 




# SPECTER-frozen-with-biblio-context-finetuned-review_classifier

This model is a fine-tuned version of allenai/specter on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2606
- eval_accuracy: 0.91
- eval_f1: 0.0925
- eval_recall: 0.0490
- eval_precision: 0.8379
- eval_runtime: 1030.2818
- eval_samples_per_second: 77.649
- eval_steps_per_second: 6.471
- epoch: 1.0
- step: 6667

## 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: 4.5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 2
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1

# SPECTER-frozen-with-biblio-context-finetuned-review_classifier

This model is a fine-tuned version of allenai/specter on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2606
- eval_accuracy: 0.91
- eval_f1: 0.0925
- eval_recall: 0.0490
- eval_precision: 0.8379
- eval_runtime: 1030.2818
- eval_samples_per_second: 77.649
- eval_steps_per_second: 6.471
- epoch: 1.0
- step: 6667 ## 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: 4.5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 2
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 # SPECTER-frozen-with-biblio-context-finetuned-review_classifier

This model is a fine-tuned version of allenai/specter on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2606
- eval_accuracy: 0.91
- eval_f1: 0.0925
- eval_recall: 0.0490
- eval_precision: 0.8379
- eval_runtime: 1030.2818
- eval_samples_per_second: 77.649
- eval_steps_per_second: 6.471
- epoch: 1.0
- step: 6667 ## 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: 4.5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 2
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
# SPECTER-frozen-with-biblio-context-finetuned-review_classifier

This model is a fine-tuned version of allenai/specter on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2606
- eval_accuracy: 0.91
- eval_f1: 0.0925
- eval_recall: 0.0490
- eval_precision: 0.8379
- eval_runtime: 1030.2818
- eval_samples_per_second: 77.649
- eval_steps_per_second: 6.471
- epoch: 1.0
- step: 6667## 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: 4.5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 2
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1