README.md

metadata

language:
  - en
license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
base_model: roberta-base
model-index:
  - name: roberta-base-sst2
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: GLUE SST2
          type: glue
          args: sst2
        metrics:
          - type: accuracy
            value: 0.9357798165137615
            name: Accuracy

roberta-base-sst2

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

• Loss: 0.2314
• Accuracy: 0.9358

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
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2287	1.0	4210	0.2314	0.9358
0.1959	2.0	8420	0.3027	0.9266
0.1635	3.0	12630	0.3022	0.9300
0.1148	4.0	16840	0.3162	0.9289

Framework versions

• Transformers 4.20.0.dev0
• Pytorch 1.11.0+cu113
• Datasets 2.1.0
• Tokenizers 0.12.1