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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
base_model: bert-base-uncased
model-index:
- name: bert-base-uncased-qqp
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- type: accuracy
value: 0.9099925797674994
name: Accuracy
- type: f1
value: 0.8788252139455897
name: F1
- task:
type: natural-language-inference
name: Natural Language Inference
dataset:
name: glue
type: glue
config: qqp
split: validation
metrics:
- type: accuracy
value: 0.9099925797674994
name: Accuracy
verified: true
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- type: precision
value: 0.8712531361415555
name: Precision
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMGM5MDdjZGY5YzE4OTg3YmJkYTgwYWMxOWY4NjhkNmE3N2YwMzc0OTc1ODQ0NjZhYjYzZDA3NTZkODczODMyYyIsInZlcnNpb24iOjF9.waQg4ueAVRbKStoFGrZrLBgWgsfmK-Ro-eHFYNLObmSbbi35hC46tjAGgNd1blHc6aNsLmpkfK-qtMCepPEEAQ
- type: recall
value: 0.8865300638226402
name: Recall
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzYyODkxZmU4ZDNjNmQ0ZGZiMTExZTA0Mjk2ZjZkMDRiNGFhOWFhNTBhNzNkMjE5YzE2MDRkN2I4YjVlMTYxZSIsInZlcnNpb24iOjF9.wXo-nBoBrXeunx-4yCbkNUfyqc8HhrJ0NeQA1d_cNBXlsNVeGEznVFduSu8aVwrrLqbRpDJWYshPEL9eAxQPAQ
- type: auc
value: 0.9690747048570257
name: AUC
verified: true
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- type: f1
value: 0.8788252139455897
name: F1
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmYyNjYxYmJmNjg3ODA1MjZmYWMxODllZGMzODI1NGFjNGU5ZTIxNGI3MWI4NWZiZDUwMDExMTE0ODEyODgyMSIsInZlcnNpb24iOjF9.a-gyRh1_YMEWnCTypkwp3w39iy5_1PmFntHszwtTISqDJtDKQsl3FYFJGzujSzllHrXl9ILFTcjLSkamvZSECw
- type: loss
value: 0.28284332156181335
name: loss
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzg5ZGJiM2E4MzI1MmZkNjAyOWFlYjU2OGI0NDJiNTI3YThiNzZkMDIwMTNhZDg1NzMwNjZmNTE5NDgzYTBiMSIsInZlcnNpb24iOjF9.CPKvNWzGTwAZf0PgU-rhQYS_sFnRmrBVor4fRzDuNQjz-QtjdCPxyfWpGVsuOzuAr_u71fdFS6tGyuVpasl1Bw
---
<!-- 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-base-uncased-qqp
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2829
- Accuracy: 0.9100
- F1: 0.8788
- Combined Score: 0.8944
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.2511 | 1.0 | 11371 | 0.2469 | 0.8969 | 0.8641 | 0.8805 |
| 0.1763 | 2.0 | 22742 | 0.2379 | 0.9071 | 0.8769 | 0.8920 |
| 0.1221 | 3.0 | 34113 | 0.2829 | 0.9100 | 0.8788 | 0.8944 |
### Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
|