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---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: add_BERT_no_pretrain_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
config: mrpc
split: validation
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.6838235294117647
- name: F1
type: f1
value: 0.8122270742358079
---
<!-- 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. -->
# add_BERT_no_pretrain_mrpc
This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6240
- Accuracy: 0.6838
- F1: 0.8122
- Combined Score: 0.7480
## 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: 0.0005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 1.154 | 1.0 | 29 | 0.6856 | 0.6838 | 0.8122 | 0.7480 |
| 0.6781 | 2.0 | 58 | 0.6609 | 0.6838 | 0.8122 | 0.7480 |
| 0.6458 | 3.0 | 87 | 0.6348 | 0.6838 | 0.8122 | 0.7480 |
| 0.6395 | 4.0 | 116 | 19.6354 | 0.3186 | 0.0071 | 0.1629 |
| 1.1486 | 5.0 | 145 | 0.6657 | 0.6838 | 0.8122 | 0.7480 |
| 0.6446 | 6.0 | 174 | 0.6277 | 0.6838 | 0.8122 | 0.7480 |
| 0.644 | 7.0 | 203 | 0.6242 | 0.6838 | 0.8122 | 0.7480 |
| 0.6337 | 8.0 | 232 | 0.6242 | 0.6838 | 0.8122 | 0.7480 |
| 0.6388 | 9.0 | 261 | 0.6253 | 0.6838 | 0.8122 | 0.7480 |
| 0.634 | 10.0 | 290 | 0.6242 | 0.6838 | 0.8122 | 0.7480 |
| 0.6346 | 11.0 | 319 | 0.6264 | 0.6838 | 0.8122 | 0.7480 |
| 0.6338 | 12.0 | 348 | 0.6273 | 0.6838 | 0.8122 | 0.7480 |
| 0.6343 | 13.0 | 377 | 0.6262 | 0.6838 | 0.8122 | 0.7480 |
| 0.6339 | 14.0 | 406 | 0.6240 | 0.6838 | 0.8122 | 0.7480 |
| 0.635 | 15.0 | 435 | 0.6244 | 0.6838 | 0.8122 | 0.7480 |
| 0.6331 | 16.0 | 464 | 0.6240 | 0.6838 | 0.8122 | 0.7480 |
| 0.6328 | 17.0 | 493 | 0.6267 | 0.6838 | 0.8122 | 0.7480 |
| 0.6338 | 18.0 | 522 | 0.6257 | 0.6838 | 0.8122 | 0.7480 |
| 0.6321 | 19.0 | 551 | 0.6240 | 0.6838 | 0.8122 | 0.7480 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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