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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-4_H-512_A-8
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_uncased_L-4_H-512_A-8_mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.7811228641171685
---
<!-- 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-4_H-512_A-8_mnli
This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5537
- Accuracy: 0.7811
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7086 | 1.0 | 1534 | 0.6315 | 0.7438 |
| 0.5704 | 2.0 | 3068 | 0.5782 | 0.7652 |
| 0.4967 | 3.0 | 4602 | 0.5685 | 0.7793 |
| 0.4356 | 4.0 | 6136 | 0.5847 | 0.7822 |
| 0.3809 | 5.0 | 7670 | 0.6004 | 0.7855 |
| 0.3341 | 6.0 | 9204 | 0.6375 | 0.7837 |
| 0.2922 | 7.0 | 10738 | 0.6666 | 0.7808 |
| 0.2565 | 8.0 | 12272 | 0.7132 | 0.7763 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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