metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: distilbert_sa_GLUE_Experiment_logit_kd_pretrain_mnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MNLI
          type: glue
          config: mnli
          split: validation_matched
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8105166802278275

distilbert_sa_GLUE_Experiment_logit_kd_pretrain_mnli

This model is a fine-tuned version of gokuls/distilbert_sa_pre-training-complete on the GLUE MNLI dataset. It achieves the following results on the evaluation set:

Loss: 0.3863
Accuracy: 0.8105

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: 256
eval_batch_size: 256
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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4379	1.0	1534	0.3984	0.7976
0.3845	2.0	3068	0.3953	0.8047
0.359	3.0	4602	0.3935	0.8102
0.3411	4.0	6136	0.3962	0.8077
0.3279	5.0	7670	0.3959	0.8172
0.3189	6.0	9204	0.4018	0.8102
0.3119	7.0	10738	0.4040	0.8073
0.3071	8.0	12272	0.3990	0.8175

Framework versions

Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.9.0
Tokenizers 0.13.2