README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: add_BERT_no_pretrain_sst2
    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: 0.5091743119266054

add_BERT_no_pretrain_sst2

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

• Loss: 0.7002
• Accuracy: 0.5092

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: 4e-05
• train_batch_size: 128
• eval_batch_size: 128
• seed: 10
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6983	1.0	527	0.6936	0.5092
0.6895	2.0	1054	0.7089	0.5092
0.6881	3.0	1581	0.6993	0.5092
0.6875	4.0	2108	0.6994	0.5092
0.6874	5.0	2635	0.6941	0.5092
0.687	6.0	3162	0.7002	0.5092

Framework versions

• Transformers 4.30.2
• Pytorch 1.14.0a0+410ce96
• Datasets 2.12.0
• Tokenizers 0.13.3