README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tecla
metrics:
  - accuracy
model-index:
  - name: roberta-base-ca-finetuned-mnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tecla
          type: tecla
          args: tecla
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7361816335412737

roberta-base-ca-finetuned-mnli

This model is a fine-tuned version of BSC-TeMU/roberta-base-ca on the tecla dataset. It achieves the following results on the evaluation set:

• Loss: 0.9354
• Accuracy: 0.7362

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
0.8465	1.0	6888	0.8222	0.6990
0.6966	2.0	13776	0.7872	0.7157
0.5643	3.0	20664	0.8060	0.7268
0.4435	4.0	27552	0.8470	0.7333
0.3206	5.0	34440	0.9354	0.7362

Framework versions

• Transformers 4.11.3
• Pytorch 1.9.0+cu111
• Datasets 1.12.1
• Tokenizers 0.10.3