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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
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
|