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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tinybert_base_train_book_ent_15p_s_init_mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.725386493083808
---
<!-- 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. -->
# tinybert_base_train_book_ent_15p_s_init_mnli
This model is a fine-tuned version of [gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init](https://huggingface.co/gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6549
- Accuracy: 0.7254
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8785 | 1.0 | 1534 | 0.7729 | 0.6660 |
| 0.7353 | 2.0 | 3068 | 0.7123 | 0.6915 |
| 0.6658 | 3.0 | 4602 | 0.6983 | 0.7073 |
| 0.6113 | 4.0 | 6136 | 0.7001 | 0.7169 |
| 0.5654 | 5.0 | 7670 | 0.6811 | 0.7245 |
| 0.5207 | 6.0 | 9204 | 0.7057 | 0.7257 |
| 0.4798 | 7.0 | 10738 | 0.7188 | 0.7291 |
| 0.4403 | 8.0 | 12272 | 0.7684 | 0.7231 |
| 0.4036 | 9.0 | 13806 | 0.8034 | 0.7165 |
| 0.3685 | 10.0 | 15340 | 0.8376 | 0.7220 |
### Framework versions
- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
|