---
library_name: transformers
language:
- en
license: apache-2.0
base_model: gokulsrinivasagan/bert_base_train_book_ent_15p_s_init
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_base_train_book_ent_15p_s_init_rte
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE RTE
      type: glue
      args: rte
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5270758122743683
---

<!-- 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_train_book_ent_15p_s_init_rte

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_train_book_ent_15p_s_init](https://huggingface.co/gokulsrinivasagan/bert_base_train_book_ent_15p_s_init) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6919
- Accuracy: 0.5271

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7023        | 1.0   | 10   | 0.6952          | 0.4729   |
| 0.7018        | 2.0   | 20   | 0.6921          | 0.5271   |
| 0.6966        | 3.0   | 30   | 0.6943          | 0.4729   |
| 0.6977        | 4.0   | 40   | 0.6960          | 0.4729   |
| 0.6969        | 5.0   | 50   | 0.6919          | 0.5271   |
| 0.7016        | 6.0   | 60   | 0.6976          | 0.4729   |
| 0.6981        | 7.0   | 70   | 0.6937          | 0.4729   |
| 0.6952        | 8.0   | 80   | 0.6928          | 0.4729   |
| 0.6986        | 9.0   | 90   | 0.6930          | 0.5271   |
| 0.6978        | 10.0  | 100  | 0.6924          | 0.5271   |


### Framework versions

- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1