metadata

license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: kd-bertBase-bertTiny
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: sst2
          split: validation
          args: sst2
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8268348623853211

kd-bertBase-bertTiny

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: 1.0591
Accuracy: 0.8268

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: 6e-05
train_batch_size: 128
eval_batch_size: 128
seed: 33
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4776	1.0	527	1.1240	0.8062
0.8442	2.0	1054	1.0475	0.8165
0.6568	3.0	1581	1.0529	0.8131
0.5623	4.0	2108	1.0503	0.8188
0.5066	5.0	2635	1.0471	0.8303
0.4736	6.0	3162	1.0711	0.8280
0.4603	7.0	3689	1.0591	0.8268

Framework versions

Transformers 4.33.3
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3