transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_tiny_lda_5_v1_book base_model:finetune:gokulsrinivasagan/bert_tiny_lda_5_v1_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_tiny_lda_5_v1_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_lda_5_v1_book_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.798781702305515
      name: Spearmanr
---

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# bert_tiny_lda_5_v1_book_stsb

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_5_v1_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_5_v1_book) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8189
- Pearson: 0.8027
- Spearmanr: 0.7988
- Combined Score: 0.8007

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.8706        | 1.0   | 23   | 2.4625          | 0.0991  | 0.1000    | 0.0995         |
| 1.7766        | 2.0   | 46   | 1.3387          | 0.6421  | 0.6371    | 0.6396         |
| 1.1649        | 3.0   | 69   | 0.9883          | 0.7530  | 0.7470    | 0.7500         |
| 0.8446        | 4.0   | 92   | 0.9501          | 0.7802  | 0.7827    | 0.7814         |
| 0.6587        | 5.0   | 115  | 0.9120          | 0.7839  | 0.7824    | 0.7831         |
| 0.5587        | 6.0   | 138  | 0.8918          | 0.7876  | 0.7880    | 0.7878         |
| 0.5104        | 7.0   | 161  | 0.9523          | 0.7822  | 0.7828    | 0.7825         |
| 0.4506        | 8.0   | 184  | 0.9421          | 0.7916  | 0.7923    | 0.7919         |
| 0.4174        | 9.0   | 207  | 1.0925          | 0.7876  | 0.7937    | 0.7906         |
| 0.3229        | 10.0  | 230  | 0.8792          | 0.7969  | 0.7946    | 0.7958         |
| 0.3096        | 11.0  | 253  | 0.9665          | 0.7887  | 0.7884    | 0.7886         |
| 0.2918        | 12.0  | 276  | 0.8212          | 0.8017  | 0.7992    | 0.8004         |
| 0.2479        | 13.0  | 299  | 0.8791          | 0.8055  | 0.8037    | 0.8046         |
| 0.2409        | 14.0  | 322  | 0.8217          | 0.7970  | 0.7930    | 0.7950         |
| 0.2071        | 15.0  | 345  | 0.8929          | 0.7998  | 0.7971    | 0.7984         |
| 0.1907        | 16.0  | 368  | 0.8189          | 0.8027  | 0.7988    | 0.8007         |
| 0.1825        | 17.0  | 391  | 0.9393          | 0.7924  | 0.7899    | 0.7912         |
| 0.1634        | 18.0  | 414  | 0.8722          | 0.8046  | 0.8023    | 0.8035         |
| 0.1531        | 19.0  | 437  | 0.9629          | 0.8037  | 0.8023    | 0.8030         |
| 0.153         | 20.0  | 460  | 1.0063          | 0.7971  | 0.7947    | 0.7959         |
| 0.1409        | 21.0  | 483  | 0.9757          | 0.7968  | 0.7942    | 0.7955         |


### Framework versions

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