README.md

metadata

license: apache-2.0
base_model: BSC-TeMU/roberta-base-bne
tags:
  - generated_from_trainer
datasets:
  - multilingual-sentiments
metrics:
  - accuracy
model-index:
  - name: roberta-base-bne-finetuned-multi-sentiment
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: multilingual-sentiments
          type: multilingual-sentiments
          config: spanish
          split: validation
          args: spanish
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7222222222222222

roberta-base-bne-finetuned-multi-sentiment

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

• Loss: 0.7635
• Accuracy: 0.7222

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6192	1.0	115	0.6712	0.7099
0.217	2.0	230	0.7635	0.7222

Framework versions

• Transformers 4.35.0
• Pytorch 1.13.1+cu117
• Datasets 2.14.6
• Tokenizers 0.14.1