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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
- accuracy
model-index:
- name: bert_base_lda_100_v1_cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
type: glue
args: cola
metrics:
- name: Matthews Correlation
type: matthews_correlation
value: 0.0
- name: Accuracy
type: accuracy
value: 0.6912751793861389
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert_base_lda_100_v1_cola
This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_100_v1) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6179
- Matthews Correlation: 0.0
- Accuracy: 0.6913
## 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 | Matthews Correlation | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6207 | 1.0 | 34 | 0.6230 | 0.0 | 0.6913 |
| 0.6135 | 2.0 | 68 | 0.6196 | 0.0 | 0.6913 |
| 0.6074 | 3.0 | 102 | 0.6179 | 0.0 | 0.6913 |
| 0.5969 | 4.0 | 136 | 0.6278 | 0.0 | 0.6913 |
| 0.5522 | 5.0 | 170 | 0.6239 | 0.0558 | 0.6616 |
| 0.4812 | 6.0 | 204 | 0.6720 | 0.1210 | 0.6846 |
| 0.416 | 7.0 | 238 | 0.7046 | 0.1010 | 0.6251 |
| 0.3693 | 8.0 | 272 | 0.8737 | 0.1050 | 0.6558 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
|