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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_tiny_lda_20_v1_qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.8355181795696265
- name: F1
type: f1
value: 0.7821386450006552
---
<!-- 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_tiny_lda_20_v1_qqp
This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_20_v1](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_20_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3641
- Accuracy: 0.8355
- F1: 0.7821
- Combined Score: 0.8088
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4896 | 1.0 | 1422 | 0.4397 | 0.7902 | 0.6817 | 0.7359 |
| 0.3891 | 2.0 | 2844 | 0.3806 | 0.8247 | 0.7674 | 0.7960 |
| 0.3332 | 3.0 | 4266 | 0.3641 | 0.8355 | 0.7821 | 0.8088 |
| 0.29 | 4.0 | 5688 | 0.3666 | 0.8448 | 0.7868 | 0.8158 |
| 0.2535 | 5.0 | 7110 | 0.3724 | 0.8485 | 0.7977 | 0.8231 |
| 0.2212 | 6.0 | 8532 | 0.3716 | 0.8517 | 0.8042 | 0.8280 |
| 0.1947 | 7.0 | 9954 | 0.4039 | 0.8528 | 0.8050 | 0.8289 |
| 0.1711 | 8.0 | 11376 | 0.4276 | 0.8535 | 0.7964 | 0.8249 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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