---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_50_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_base_lda_50_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: 0.5018050541516246
---

<!-- 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_50_v1_book_rte

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_50_v1_book](https://huggingface.co./gokulsrinivasagan/bert_base_lda_50_v1_book) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6885
- Accuracy: 0.5018

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7099        | 1.0   | 10   | 0.7059          | 0.5343   |
| 0.6998        | 2.0   | 20   | 0.6954          | 0.4657   |
| 0.6965        | 3.0   | 30   | 0.6918          | 0.5271   |
| 0.6924        | 4.0   | 40   | 0.6914          | 0.5271   |
| 0.6932        | 5.0   | 50   | 0.6946          | 0.5271   |
| 0.6962        | 6.0   | 60   | 0.6998          | 0.4765   |
| 0.6918        | 7.0   | 70   | 0.6885          | 0.5018   |
| 0.6802        | 8.0   | 80   | 0.7132          | 0.5523   |
| 0.6651        | 9.0   | 90   | 0.6924          | 0.5523   |
| 0.6437        | 10.0  | 100  | 0.8075          | 0.5054   |
| 0.6004        | 11.0  | 110  | 0.7967          | 0.5451   |
| 0.518         | 12.0  | 120  | 0.8455          | 0.5451   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3