---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_20_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_tiny_lda_20_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: 0.6550260104726466
---

<!-- 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. -->

# bert_tiny_lda_20_v1_book_stsb

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_20_v1_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_20_v1_book) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3015
- Pearson: 0.6652
- Spearmanr: 0.6550
- Combined Score: 0.6601

## 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 | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.0179        | 1.0   | 23   | 2.6080          | 0.0861  | 0.0929    | 0.0895         |
| 2.035         | 2.0   | 46   | 2.3616          | 0.2683  | 0.2477    | 0.2580         |
| 1.5507        | 3.0   | 69   | 2.0235          | 0.4102  | 0.3826    | 0.3964         |
| 1.2619        | 4.0   | 92   | 1.7173          | 0.5300  | 0.5095    | 0.5198         |
| 1.0353        | 5.0   | 115  | 1.5564          | 0.5829  | 0.5638    | 0.5733         |
| 0.9021        | 6.0   | 138  | 1.3864          | 0.6315  | 0.6213    | 0.6264         |
| 0.7466        | 7.0   | 161  | 1.4336          | 0.6263  | 0.6143    | 0.6203         |
| 0.6538        | 8.0   | 184  | 1.3015          | 0.6652  | 0.6550    | 0.6601         |
| 0.5925        | 9.0   | 207  | 1.3561          | 0.6456  | 0.6322    | 0.6389         |
| 0.5308        | 10.0  | 230  | 1.5712          | 0.6372  | 0.6248    | 0.6310         |
| 0.4724        | 11.0  | 253  | 1.4731          | 0.6424  | 0.6304    | 0.6364         |
| 0.4354        | 12.0  | 276  | 1.4500          | 0.6696  | 0.6567    | 0.6632         |
| 0.3707        | 13.0  | 299  | 1.3024          | 0.6771  | 0.6673    | 0.6722         |


### Framework versions

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