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---
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
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