---
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
- f1
model-index:
- name: bert_base_train_book_ent_15p_s_init_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6838235294117647
    - name: F1
      type: f1
      value: 0.8122270742358079
---

<!-- 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_mrpc

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 MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6236
- Accuracy: 0.6838
- F1: 0.8122
- Combined Score: 0.7480

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6428        | 1.0   | 15   | 0.6255          | 0.6838   | 0.8122 | 0.7480         |
| 0.6363        | 2.0   | 30   | 0.6297          | 0.6838   | 0.8122 | 0.7480         |
| 0.6317        | 3.0   | 45   | 0.6301          | 0.6838   | 0.8122 | 0.7480         |
| 0.6411        | 4.0   | 60   | 0.6255          | 0.6838   | 0.8122 | 0.7480         |
| 0.6336        | 5.0   | 75   | 0.6254          | 0.6838   | 0.8122 | 0.7480         |
| 0.6348        | 6.0   | 90   | 0.6239          | 0.6838   | 0.8122 | 0.7480         |
| 0.6346        | 7.0   | 105  | 0.6236          | 0.6838   | 0.8122 | 0.7480         |
| 0.6364        | 8.0   | 120  | 0.6242          | 0.6838   | 0.8122 | 0.7480         |
| 0.6309        | 9.0   | 135  | 0.6321          | 0.6838   | 0.8122 | 0.7480         |
| 0.6392        | 10.0  | 150  | 0.6242          | 0.6838   | 0.8122 | 0.7480         |
| 0.6353        | 11.0  | 165  | 0.6271          | 0.6838   | 0.8122 | 0.7480         |
| 0.6339        | 12.0  | 180  | 0.6260          | 0.6838   | 0.8122 | 0.7480         |


### Framework versions

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