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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_lda_50_v1_qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: glue
args: qnli
metrics:
- name: Accuracy
type: accuracy
value: 0.8211605345048508
---
<!-- 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_qnli
This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_50_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_50_v1) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4075
- Accuracy: 0.8212
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5532 | 1.0 | 410 | 0.5177 | 0.7628 |
| 0.4263 | 2.0 | 820 | 0.4075 | 0.8212 |
| 0.3371 | 3.0 | 1230 | 0.4169 | 0.8133 |
| 0.2505 | 4.0 | 1640 | 0.4766 | 0.8116 |
| 0.18 | 5.0 | 2050 | 0.6080 | 0.7941 |
| 0.1275 | 6.0 | 2460 | 0.6769 | 0.8120 |
| 0.0953 | 7.0 | 2870 | 0.6988 | 0.7974 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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