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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_20_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_tiny_lda_20_v1_book_rte
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glue
args: rte
metrics:
- name: Accuracy
type: accuracy
value: 0.5342960288808665
---
<!-- 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_book_rte
This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_20_v1_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_20_v1_book) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6854
- Accuracy: 0.5343
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7071 | 1.0 | 10 | 0.6985 | 0.4693 |
| 0.6942 | 2.0 | 20 | 0.6904 | 0.5487 |
| 0.6872 | 3.0 | 30 | 0.6893 | 0.5379 |
| 0.6791 | 4.0 | 40 | 0.6854 | 0.5343 |
| 0.6633 | 5.0 | 50 | 0.7277 | 0.5523 |
| 0.6418 | 6.0 | 60 | 0.6989 | 0.5415 |
| 0.5818 | 7.0 | 70 | 0.7711 | 0.5379 |
| 0.5207 | 8.0 | 80 | 0.7769 | 0.5596 |
| 0.419 | 9.0 | 90 | 0.8660 | 0.5307 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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