---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_olda_book_10_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_tiny_olda_book_10_v1_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.7894827878783358
---

<!-- 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_olda_book_10_v1_stsb

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_olda_book_10_v1](https://huggingface.co./gokulsrinivasagan/bert_tiny_olda_book_10_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8800
- Pearson: 0.7899
- Spearmanr: 0.7895
- Combined Score: 0.7897

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.0028        | 1.0   | 23   | 2.5219          | 0.1644  | 0.1637    | 0.1641         |
| 1.7825        | 2.0   | 46   | 1.7353          | 0.6315  | 0.6561    | 0.6438         |
| 1.2017        | 3.0   | 69   | 1.1421          | 0.7243  | 0.7369    | 0.7306         |
| 0.8992        | 4.0   | 92   | 1.0970          | 0.7550  | 0.7677    | 0.7613         |
| 0.6849        | 5.0   | 115  | 0.8800          | 0.7899  | 0.7895    | 0.7897         |
| 0.5834        | 6.0   | 138  | 0.8918          | 0.7965  | 0.7978    | 0.7972         |
| 0.4852        | 7.0   | 161  | 0.9756          | 0.7948  | 0.7965    | 0.7957         |
| 0.4346        | 8.0   | 184  | 0.8957          | 0.7867  | 0.7860    | 0.7864         |
| 0.3871        | 9.0   | 207  | 0.9086          | 0.7900  | 0.7882    | 0.7891         |
| 0.3449        | 10.0  | 230  | 1.0219          | 0.7874  | 0.7899    | 0.7886         |


### Framework versions

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