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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-2_H-512_A-8
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_uncased_L-2_H-512_A-8_qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: glue
args: qnli
metrics:
- name: Accuracy
type: accuracy
value: 0.8405637927878455
---
<!-- 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_uncased_L-2_H-512_A-8_qnli
This model is a fine-tuned version of [google/bert_uncased_L-2_H-512_A-8](https://huggingface.co/google/bert_uncased_L-2_H-512_A-8) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3808
- Accuracy: 0.8406
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4759 | 1.0 | 410 | 0.4065 | 0.8219 |
| 0.4 | 2.0 | 820 | 0.3840 | 0.8309 |
| 0.3491 | 3.0 | 1230 | 0.3808 | 0.8406 |
| 0.3005 | 4.0 | 1640 | 0.4054 | 0.8340 |
| 0.256 | 5.0 | 2050 | 0.4341 | 0.8334 |
| 0.215 | 6.0 | 2460 | 0.4468 | 0.8321 |
| 0.182 | 7.0 | 2870 | 0.5106 | 0.8288 |
| 0.1543 | 8.0 | 3280 | 0.5216 | 0.8298 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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