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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_wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: glue
args: wnli
metrics:
- name: Accuracy
type: accuracy
value: 0.4507042253521127
---
<!-- 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_wnli
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 WNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7026
- Accuracy: 0.4507
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.709 | 1.0 | 3 | 0.7026 | 0.4507 |
| 0.6989 | 2.0 | 6 | 0.7127 | 0.4085 |
| 0.6959 | 3.0 | 9 | 0.7356 | 0.3239 |
| 0.692 | 4.0 | 12 | 0.7549 | 0.3099 |
| 0.6833 | 5.0 | 15 | 0.7649 | 0.2817 |
| 0.6881 | 6.0 | 18 | 0.7724 | 0.2958 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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