metadata

library_name: transformers
language:
  - en
base_model: gokulsrinivasagan/bert_tiny_lda_20_v1
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: bert_tiny_lda_20_v1_mnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MNLI
          type: glue
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.3522172497965826

bert_tiny_lda_20_v1_mnli

This model is a fine-tuned version of gokulsrinivasagan/bert_tiny_lda_20_v1 on the GLUE MNLI dataset. It achieves the following results on the evaluation set:

Loss: 1.0962
Accuracy: 0.3522

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: 0.001
train_batch_size: 256
eval_batch_size: 256
seed: 10
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0993	1.0	1534	1.0993	0.3274
1.0986	2.0	3068	1.0962	0.3545
1.0987	3.0	4602	1.0964	0.3274
1.0985	4.0	6136	1.1016	0.3182
1.0985	5.0	7670	1.0989	0.3545
1.0986	6.0	9204	1.0989	0.3545
1.0986	7.0	10738	1.0993	0.3182

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3