metadata
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_base_lda_20_v1_qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: glue
args: qnli
metrics:
- name: Accuracy
type: accuracy
value: 0.7230459454512173
bert_base_lda_20_v1_qnli
This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda_20_v1 on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.5702
- Accuracy: 0.7230
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 |
|---|---|---|---|---|
| 0.6969 | 1.0 | 410 | 0.7003 | 0.4946 |
| 0.6528 | 2.0 | 820 | 0.6001 | 0.6769 |
| 0.5423 | 3.0 | 1230 | 0.5868 | 0.6800 |
| 0.4379 | 4.0 | 1640 | 0.5702 | 0.7230 |
| 0.354 | 5.0 | 2050 | 0.6331 | 0.7183 |
| 0.2797 | 6.0 | 2460 | 0.7638 | 0.7091 |
| 0.2193 | 7.0 | 2870 | 0.8051 | 0.7058 |
| 0.1732 | 8.0 | 3280 | 0.8758 | 0.7190 |
| 0.1391 | 9.0 | 3690 | 0.9915 | 0.7066 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3