README.md

metadata

language:
  - en
license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - matthews_correlation
model-index:
  - name: roberta-base-cola
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE COLA
          type: glue
          args: cola
        metrics:
          - name: Matthews Correlation
            type: matthews_correlation
            value: 0.6232164195970928
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: glue
          type: glue
          config: cola
          split: validation
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8456375838926175
            verified: true
          - name: Precision Macro
            type: precision
            value: 0.843528494100156
            verified: true
          - name: Precision Micro
            type: precision
            value: 0.8456375838926175
            verified: true
          - name: Precision Weighted
            type: precision
            value: 0.8450074516171895
            verified: true
          - name: Recall Macro
            type: recall
            value: 0.7826539226919134
            verified: true
          - name: Recall Micro
            type: recall
            value: 0.8456375838926175
            verified: true
          - name: Recall Weighted
            type: recall
            value: 0.8456375838926175
            verified: true
          - name: F1 Macro
            type: f1
            value: 0.8032750971481726
            verified: true
          - name: F1 Micro
            type: f1
            value: 0.8456375838926175
            verified: true
          - name: F1 Weighted
            type: f1
            value: 0.838197890972622
            verified: true
          - name: loss
            type: loss
            value: 1.0575031042099
            verified: true

roberta-base-cola

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

• Loss: 1.0571
• Matthews Correlation: 0.6232

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	Matthews Correlation
0.5497	1.0	535	0.5504	0.4613
0.3786	2.0	1070	0.4850	0.5470
0.2733	3.0	1605	0.5036	0.5792
0.2204	4.0	2140	0.5532	0.6139
0.164	5.0	2675	0.9516	0.5934
0.1351	6.0	3210	0.9051	0.5754
0.1065	7.0	3745	0.9006	0.6161
0.0874	8.0	4280	0.9457	0.6157
0.0579	9.0	4815	1.0372	0.6007
0.0451	10.0	5350	1.0571	0.6232

Framework versions

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