metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: bert-tiny-finetuned-glue-rte
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: rte
          split: train
          args: rte
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.592057761732852

bert-tiny-finetuned-glue-rte

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the glue dataset. It achieves the following results on the evaluation set:

Loss: 0.6726
Accuracy: 0.5921

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
No log	1.0	156	0.6861	0.5596
No log	2.0	312	0.6809	0.5596
No log	3.0	468	0.6771	0.5632
0.6808	4.0	624	0.6735	0.5812
0.6808	5.0	780	0.6726	0.5921

Framework versions

Transformers 4.21.0
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1