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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_sa_GLUE_Experiment_data_aug_qqp_256
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.7887954489240663
- name: F1
type: f1
value: 0.7301115711621732
---
<!-- 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. -->
# distilbert_sa_GLUE_Experiment_data_aug_qqp_256
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5126
- Accuracy: 0.7888
- F1: 0.7301
- Combined Score: 0.7595
## 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
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:--------------:|
| 0.3952 | 1.0 | 29671 | 0.5126 | 0.7888 | 0.7301 | 0.7595 |
| 0.2233 | 2.0 | 59342 | 0.5941 | 0.7960 | 0.7346 | 0.7653 |
| 0.147 | 3.0 | 89013 | 0.6603 | 0.7997 | 0.7340 | 0.7668 |
| 0.1067 | 4.0 | 118684 | 0.7091 | 0.8012 | 0.7376 | 0.7694 |
| 0.082 | 5.0 | 148355 | 0.8757 | 0.8000 | 0.7377 | 0.7688 |
| 0.0652 | 6.0 | 178026 | 0.8332 | 0.8044 | 0.7379 | 0.7711 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
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