---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-finetuned-mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.8602941176470589
      name: Accuracy
    - type: f1
      value: 0.9032258064516129
      name: F1
  - task:
      type: natural-language-inference
      name: Natural Language Inference
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: validation
    metrics:
    - type: accuracy
      value: 0.8602941176470589
      name: Accuracy
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDBkNTFiZTMwNDUzMTcwM2M3ZGRkNGU4OTAzNWU3OGI4OWI3ZDNkOWM3NTY5NjMzYTA3MGEzNmI3ZDdlZjc1NiIsInZlcnNpb24iOjF9.PHE4--RyyOTkZ5taAbFYrKOR1RXEeufilEHfGrkQLChupGmtkZOM1zeNOpD2oXHjFDCtAAvW0QNDg2o4ZilBBA
    - type: precision
      value: 0.8580645161290322
      name: Precision
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYmIyMDczODQ4MmRjYzJkMTU2MzcwZjEzNzVjMjk3NGFhOWNkOTE5MzJhYjBmYzQ4YmI4NDM5YTI4Y2M3MTRkYyIsInZlcnNpb24iOjF9.T12Muvex24JeP2_LYJLZK2L9j4oBhlN-sBkRJVb0qLNMY3e5n6v8T_AJBogzi1jHexLd4XxwEY1Hy0QSkJRmDw
    - type: recall
      value: 0.953405017921147
      name: Recall
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTU4Zjg4YjgwYmYyYjZlOTIwNDkyNTk2YWQ5YTJiNDQ0OTIyNTE4YTg5ZTNmNzRjNzgyNzE2NTI1YzhjMzJjNyIsInZlcnNpb24iOjF9.A2SNduak8mRBenH-XukaaS0QnxVDT6FzO2hgXzUFvCwfLv3zBDeNY-a87gPED_J0WF9iwN3X5Ebe4S2cKMAgAA
    - type: auc
      value: 0.9257731099441527
      name: AUC
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYmI1NTE3YzBmYTQ2MDMxMTg0Y2NkYmIwNjM2ZWY4MWVmNGI0NjQ0YTZhYzFiMWNiNTA2ODA0YTA3ZDdkYjMyMyIsInZlcnNpb24iOjF9.1R69m5DXLgazlFfznzfNwg_aVKNcPw058bzYeh0ZdJ17nITKyST0pzvSSXtU8TdS-6-e3sWxgcMR_HyJ5o9eBQ
    - type: f1
      value: 0.9032258064516129
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDIyMzc1ZDY5N2MyZjFiNzU5M2E2MjVhMGE4Njk1OGNiYmMyMGFiYjJmZjcyMmU2MWFmMWM2MWQzNTNmNDkyYSIsInZlcnNpb24iOjF9._v8lz1SCg2pTKeaZz3LHDeHEsrM5dVFA_oLODv4beZg9vxS3kY3AzHf69n_Sy9B7Vd7Oam656fMH1K_409RoAA
    - type: loss
      value: 0.5150377154350281
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTYxMjYzNzFkYWU0NjY0MTFiYmViMzI2YTA0ODNlZjhiMjJkZWEyNjlhODA5ZWY1NjM4ODNmYTdjYzI2NTJmZCIsInZlcnNpb24iOjF9.ilV_XdBmf1Qb0wnhPux_RWJft0Bj3WnYv0vdEb3ysAUQ0pcFlYe-S2SaLjQguKrILTB8w9q0MOGle0AZYXOACg
---

<!-- 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