README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: bert-base-cased-finetuned-sst2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE SST2
          type: glue
          args: sst2
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9231651376146789

bert-base-cased-finetuned-sst2

This model is a fine-tuned version of bert-base-cased on the GLUE SST2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3649
• Accuracy: 0.9232

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.233	1.0	4210	0.9174	0.2841
0.1261	2.0	8420	0.9278	0.3310
0.0768	3.0	12630	0.9232	0.3649

Framework versions

• Transformers 4.11.0.dev0
• Pytorch 1.9.0
• Datasets 1.12.1
• Tokenizers 0.10.3