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---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- quora
metrics:
- accuracy
model-index:
- name: qqp_v2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: quora
type: quora
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9073190036854732
---
<!-- 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. -->
# qqp_v2
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the quora dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2537
- Accuracy: 0.9073
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2591 | 1.0 | 5054 | 0.2429 | 0.8948 |
| 0.186 | 2.0 | 10108 | 0.2342 | 0.9058 |
| 0.1349 | 3.0 | 15162 | 0.2537 | 0.9073 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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