metadata

tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model_index:
  - name: hackMIT-finetuned-sst2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: sst2
        metric:
          name: Accuracy
          type: accuracy
          value: 0.8027522935779816

hackMIT-finetuned-sst2

This model is a fine-tuned version of Blaine-Mason/hackMIT-finetuned-sst2 on the glue dataset. It achieves the following results on the evaluation set:

Loss: 1.1086
Accuracy: 0.8028

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: 2.033238621168611e-06
train_batch_size: 16
eval_batch_size: 8
seed: 30
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0674	1.0	4210	1.1086	0.8028

Framework versions

Transformers 4.9.2
Pytorch 1.9.0+cu102
Datasets 1.11.0
Tokenizers 0.10.3