metadata
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_tiny_lda_100_v1_qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: glue
args: qnli
metrics:
- name: Accuracy
type: accuracy
value: 0.727622185612301
bert_tiny_lda_100_v1_qnli
This model is a fine-tuned version of gokulsrinivasagan/bert_tiny_lda_100_v1 on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.5783
- Accuracy: 0.7276
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
- 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 |
|---|---|---|---|---|
| 0.6638 | 1.0 | 410 | 0.6427 | 0.6251 |
| 0.6373 | 2.0 | 820 | 0.6345 | 0.6341 |
| 0.5861 | 3.0 | 1230 | 0.5895 | 0.6809 |
| 0.4866 | 4.0 | 1640 | 0.5783 | 0.7276 |
| 0.4086 | 5.0 | 2050 | 0.5973 | 0.7212 |
| 0.3472 | 6.0 | 2460 | 0.5946 | 0.7375 |
| 0.2941 | 7.0 | 2870 | 0.7428 | 0.7174 |
| 0.2498 | 8.0 | 3280 | 0.6952 | 0.7382 |
| 0.209 | 9.0 | 3690 | 0.7845 | 0.7293 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3