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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_100_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_tiny_lda_100_v1_book_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.7475490196078431
- name: F1
type: f1
value: 0.8303130148270182
---
<!-- 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_100_v1_book_mrpc
This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_100_v1_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1_book) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5396
- Accuracy: 0.7475
- F1: 0.8303
- Combined Score: 0.7889
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.62 | 1.0 | 15 | 0.5966 | 0.6740 | 0.7892 | 0.7316 |
| 0.5856 | 2.0 | 30 | 0.5702 | 0.7010 | 0.8129 | 0.7569 |
| 0.5467 | 3.0 | 45 | 0.5471 | 0.7279 | 0.8195 | 0.7737 |
| 0.4866 | 4.0 | 60 | 0.5721 | 0.7426 | 0.8331 | 0.7879 |
| 0.4174 | 5.0 | 75 | 0.5396 | 0.7475 | 0.8303 | 0.7889 |
| 0.3418 | 6.0 | 90 | 0.5986 | 0.75 | 0.8211 | 0.7855 |
| 0.2528 | 7.0 | 105 | 0.6746 | 0.6985 | 0.7593 | 0.7289 |
| 0.1784 | 8.0 | 120 | 0.6922 | 0.7304 | 0.7925 | 0.7614 |
| 0.1522 | 9.0 | 135 | 0.7651 | 0.7574 | 0.8395 | 0.7984 |
| 0.1123 | 10.0 | 150 | 0.7805 | 0.7574 | 0.8308 | 0.7941 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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