README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model_index:
  - name: bert-base-uncased-finetuned-sst2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: sst2
        metric:
          name: Accuracy
          type: accuracy
          value: 0.930045871559633

bert-base-uncased-finetuned-sst2

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

• Loss: 0.3865
• Accuracy: 0.9300

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.179	1.0	4210	0.2863	0.9197
0.1251	2.0	8420	0.3202	0.9186
0.0816	3.0	12630	0.3339	0.9243
0.067	4.0	16840	0.3108	0.9289
0.0337	5.0	21050	0.3865	0.9300

Framework versions

• Transformers 4.9.1
• Pytorch 1.9.0+cu102
• Datasets 1.11.0
• Tokenizers 0.10.3