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metadata
license: apache-2.0
tags:
  - classifier
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: deep_model_09_clasificador-news-2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: ag_news
          type: ag_news
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9033149171270718

deep_model_09_clasificador-news-2

This model is a fine-tuned version of albert-base-v2 on the ag_news dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4530
  • Accuracy: 0.9033

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6332 1.0 715 0.4676 0.8812
0.5148 2.0 1430 0.4496 0.9006
0.3638 3.0 2145 0.4530 0.9033

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3