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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_lda_50_v1_qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.8596339351966361
- name: F1
type: f1
value: 0.8195720598988967
---
<!-- 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_lda_50_v1_qqp
This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_50_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_50_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3144
- Accuracy: 0.8596
- F1: 0.8196
- Combined Score: 0.8396
## 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
- 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4097 | 1.0 | 1422 | 0.3464 | 0.8409 | 0.7811 | 0.8110 |
| 0.3001 | 2.0 | 2844 | 0.3144 | 0.8596 | 0.8196 | 0.8396 |
| 0.2371 | 3.0 | 4266 | 0.3187 | 0.8675 | 0.8278 | 0.8477 |
| 0.1845 | 4.0 | 5688 | 0.3464 | 0.8678 | 0.8117 | 0.8397 |
| 0.1427 | 5.0 | 7110 | 0.3925 | 0.8726 | 0.8199 | 0.8463 |
| 0.1113 | 6.0 | 8532 | 0.3813 | 0.8747 | 0.8305 | 0.8526 |
| 0.0887 | 7.0 | 9954 | 0.4306 | 0.8746 | 0.8354 | 0.8550 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
|