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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
base_model: albert-base-v2
model-index:
  - name: albert-base-v2-finetuned-rte
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: glue
          type: glue
          args: rte
        metrics:
          - type: accuracy
            value: 0.7581227436823105
            name: Accuracy

albert-base-v2-finetuned-rte

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

  • Loss: 1.2496
  • Accuracy: 0.7581

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: 10
  • eval_batch_size: 10
  • 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
No log 1.0 249 0.5914 0.6751
No log 2.0 498 0.5843 0.7184
0.5873 3.0 747 0.6925 0.7220
0.5873 4.0 996 1.1613 0.7545
0.2149 5.0 1245 1.2496 0.7581

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.0
  • Tokenizers 0.10.3