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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-2_H-256_A-4
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_uncased_L-2_H-256_A-4_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.7475490196078431
- name: F1
type: f1
value: 0.835725677830941
---
<!-- 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-256_A-4_mrpc
This model is a fine-tuned version of [google/bert_uncased_L-2_H-256_A-4](https://huggingface.co/google/bert_uncased_L-2_H-256_A-4) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5344
- Accuracy: 0.7475
- F1: 0.8357
- Combined Score: 0.7916
## 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 | F1 | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.619 | 1.0 | 15 | 0.5956 | 0.6887 | 0.8146 | 0.7517 |
| 0.5893 | 2.0 | 30 | 0.5835 | 0.7010 | 0.8179 | 0.7594 |
| 0.5612 | 3.0 | 45 | 0.5597 | 0.7059 | 0.8171 | 0.7615 |
| 0.5397 | 4.0 | 60 | 0.5398 | 0.7377 | 0.8320 | 0.7849 |
| 0.5063 | 5.0 | 75 | 0.5358 | 0.7426 | 0.8336 | 0.7881 |
| 0.476 | 6.0 | 90 | 0.5344 | 0.7475 | 0.8357 | 0.7916 |
| 0.4361 | 7.0 | 105 | 0.5515 | 0.7451 | 0.8349 | 0.7900 |
| 0.4014 | 8.0 | 120 | 0.5508 | 0.75 | 0.8365 | 0.7933 |
| 0.3684 | 9.0 | 135 | 0.5901 | 0.7304 | 0.8254 | 0.7779 |
| 0.3396 | 10.0 | 150 | 0.5755 | 0.7426 | 0.8276 | 0.7851 |
| 0.3061 | 11.0 | 165 | 0.5943 | 0.75 | 0.8317 | 0.7908 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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