---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_100_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: distilbert_lda_100_v1_book_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.8014167289188371
---

<!-- 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_100_v1_book_stsb

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_100_v1_book](https://huggingface.co/gokulsrinivasagan/distilbert_lda_100_v1_book) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7981
- Pearson: 0.8060
- Spearmanr: 0.8014
- Combined Score: 0.8037

## 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 OptimizerNames.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 | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.1376        | 1.0   | 23   | 2.3444          | 0.1800  | 0.1657    | 0.1729         |
| 1.571         | 2.0   | 46   | 1.4977          | 0.6469  | 0.6552    | 0.6511         |
| 1.0298        | 3.0   | 69   | 0.9940          | 0.7483  | 0.7462    | 0.7472         |
| 0.8795        | 4.0   | 92   | 1.0649          | 0.7622  | 0.7710    | 0.7666         |
| 0.6951        | 5.0   | 115  | 1.5036          | 0.7508  | 0.7848    | 0.7678         |
| 0.5558        | 6.0   | 138  | 0.9067          | 0.7878  | 0.7914    | 0.7896         |
| 0.4306        | 7.0   | 161  | 0.8333          | 0.8051  | 0.8039    | 0.8045         |
| 0.3592        | 8.0   | 184  | 0.9582          | 0.7967  | 0.7975    | 0.7971         |
| 0.2847        | 9.0   | 207  | 1.0402          | 0.7929  | 0.7954    | 0.7942         |
| 0.2689        | 10.0  | 230  | 0.7981          | 0.8060  | 0.8014    | 0.8037         |
| 0.2368        | 11.0  | 253  | 0.8628          | 0.8101  | 0.8083    | 0.8092         |
| 0.2088        | 12.0  | 276  | 1.0529          | 0.7991  | 0.8011    | 0.8001         |
| 0.1912        | 13.0  | 299  | 0.8878          | 0.8011  | 0.8013    | 0.8012         |
| 0.1618        | 14.0  | 322  | 0.8757          | 0.7959  | 0.7943    | 0.7951         |
| 0.1557        | 15.0  | 345  | 0.8971          | 0.8001  | 0.7979    | 0.7990         |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1