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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_100_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_lda_100_v1_book_qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.8904279000742024
- name: F1
type: f1
value: 0.8545442605726294
---
<!-- 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_book_qqp
This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_100_v1_book](https://huggingface.co/gokulsrinivasagan/bert_base_lda_100_v1_book) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2750
- Accuracy: 0.8904
- F1: 0.8545
- Combined Score: 0.8725
## 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 | F1 | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.3622 | 1.0 | 1422 | 0.2906 | 0.8715 | 0.8262 | 0.8489 |
| 0.2502 | 2.0 | 2844 | 0.2915 | 0.8744 | 0.8442 | 0.8593 |
| 0.1834 | 3.0 | 4266 | 0.2750 | 0.8904 | 0.8545 | 0.8725 |
| 0.1335 | 4.0 | 5688 | 0.3052 | 0.8926 | 0.8529 | 0.8728 |
| 0.0997 | 5.0 | 7110 | 0.3534 | 0.8940 | 0.8548 | 0.8744 |
| 0.076 | 6.0 | 8532 | 0.3856 | 0.8918 | 0.8551 | 0.8735 |
| 0.0618 | 7.0 | 9954 | 0.4014 | 0.8911 | 0.8592 | 0.8752 |
| 0.0508 | 8.0 | 11376 | 0.4139 | 0.8910 | 0.8597 | 0.8754 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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