README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - null
metrics:
  - accuracy
model-index:
  - name: roberta-base-bne-finetuned-mnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9607097303206997

roberta-base-bne-finetuned-mnli

This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1657
• Accuracy: 0.9607

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: 4

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.1512	1.0	22227	0.9501	0.1418
0.1253	2.0	44454	0.9567	0.1499
0.0973	3.0	66681	0.9594	0.1397
0.0658	4.0	88908	0.9607	0.1657

Framework versions

• Transformers 4.10.3
• Pytorch 1.9.0+cu102
• Datasets 1.12.1
• Tokenizers 0.10.3