---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_5_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_lda_5_v1_rte
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE RTE
      type: glue
      args: rte
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5270758122743683
---

<!-- 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_5_v1_rte

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_5_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_5_v1) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6916
- Accuracy: 0.5271

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9449        | 1.0   | 10   | 0.7022          | 0.5271   |
| 0.7042        | 2.0   | 20   | 0.7000          | 0.4729   |
| 0.7004        | 3.0   | 30   | 0.6919          | 0.5271   |
| 0.6962        | 4.0   | 40   | 0.6929          | 0.5271   |
| 0.6965        | 5.0   | 50   | 0.6996          | 0.5271   |
| 0.6965        | 6.0   | 60   | 0.6918          | 0.5271   |
| 0.6947        | 7.0   | 70   | 0.6916          | 0.5271   |
| 0.6949        | 8.0   | 80   | 0.6938          | 0.4729   |
| 0.6948        | 9.0   | 90   | 0.6991          | 0.4729   |
| 0.6957        | 10.0  | 100  | 0.6920          | 0.5271   |
| 0.6941        | 11.0  | 110  | 0.6956          | 0.4729   |
| 0.6944        | 12.0  | 120  | 0.6935          | 0.4729   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3