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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.8602941176470589
- name: F1
type: f1
value: 0.9032258064516129
- task:
type: natural-language-inference
name: Natural Language Inference
dataset:
name: glue
type: glue
config: mrpc
split: validation
metrics:
- name: Accuracy
type: accuracy
value: 0.8602941176470589
verified: true
- name: Precision
type: precision
value: 0.8580645161290322
verified: true
- name: Recall
type: recall
value: 0.953405017921147
verified: true
- name: AUC
type: auc
value: 0.9257731099441527
verified: true
- name: F1
type: f1
value: 0.9032258064516129
verified: true
- name: loss
type: loss
value: 0.5150377154350281
verified: true
---
<!-- 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-finetuned-mrpc
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5152
- Accuracy: 0.8603
- F1: 0.9032
- Combined Score: 0.8818
## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| No log | 1.0 | 230 | 0.3668 | 0.8431 | 0.8881 | 0.8656 |
| No log | 2.0 | 460 | 0.3751 | 0.8578 | 0.9017 | 0.8798 |
| 0.4264 | 3.0 | 690 | 0.5152 | 0.8603 | 0.9032 | 0.8818 |
### Framework versions
- Transformers 4.11.0.dev0
- Pytorch 1.8.1+cu111
- Datasets 1.10.3.dev0
- Tokenizers 0.10.3
|