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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-large-cased-finetuned-wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: glue
args: wnli
metrics:
- name: Accuracy
type: accuracy
value: 0.352112676056338
---
<!-- 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-large-cased-finetuned-wnli
This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the GLUE WNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7087
- Accuracy: 0.3521
## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 0.7114 | 1.0 | 159 | 0.5634 | 0.6923 |
| 0.7141 | 2.0 | 318 | 0.5634 | 0.6895 |
| 0.7063 | 3.0 | 477 | 0.5634 | 0.6930 |
| 0.712 | 4.0 | 636 | 0.4507 | 0.7077 |
| 0.7037 | 5.0 | 795 | 0.3521 | 0.7087 |
### Framework versions
- Transformers 4.11.0.dev0
- Pytorch 1.9.0
- Datasets 1.12.1
- Tokenizers 0.10.3
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