metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - f1
  - accuracy
model-index:
  - name: glue_sst_classifier
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: sst2
        metrics:
          - name: F1
            type: f1
            value: 0.9033707865168539
          - name: Accuracy
            type: accuracy
            value: 0.9013761467889908

glue_sst_classifier

This model is a fine-tuned version of bert-base-cased on the glue dataset. It achieves the following results on the evaluation set:

Loss: 0.2359
F1: 0.9034
Accuracy: 0.9014

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: 1e-05
train_batch_size: 128
eval_batch_size: 128
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: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.3653	0.19	100	0.3213	0.8717	0.8727
0.291	0.38	200	0.2662	0.8936	0.8911
0.2239	0.57	300	0.2417	0.9081	0.9060
0.2306	0.76	400	0.2359	0.9105	0.9094
0.2185	0.95	500	0.2371	0.9011	0.8991

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1