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_wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: glue
args: wnli
metrics:
- name: Accuracy
type: accuracy
value: 0.5633802816901409
bert_base_lda_20_v1_wnli
This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda_20_v1 on the GLUE WNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6815
- Accuracy: 0.5634
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 |
|---|---|---|---|---|
| 0.8433 | 1.0 | 3 | 0.7335 | 0.4366 |
| 0.7419 | 2.0 | 6 | 0.7790 | 0.4366 |
| 0.7237 | 3.0 | 9 | 0.6986 | 0.5634 |
| 0.7156 | 4.0 | 12 | 0.7406 | 0.4507 |
| 0.7143 | 5.0 | 15 | 0.6858 | 0.5634 |
| 0.6989 | 6.0 | 18 | 0.6855 | 0.5634 |
| 0.6949 | 7.0 | 21 | 0.6932 | 0.5070 |
| 0.6949 | 8.0 | 24 | 0.6815 | 0.5634 |
| 0.6963 | 9.0 | 27 | 0.6960 | 0.4930 |
| 0.6932 | 10.0 | 30 | 0.6830 | 0.5352 |
| 0.6989 | 11.0 | 33 | 0.6838 | 0.5352 |
| 0.6969 | 12.0 | 36 | 0.7047 | 0.4930 |
| 0.7032 | 13.0 | 39 | 0.6939 | 0.5070 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3