transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_tiny_olda_book_5_v1 base_model:finetune:gokulsrinivasagan/bert_tiny_olda_book_5_v1 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_tiny_olda_book_5_v1
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_olda_book_5_v1_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.3909057078280815
      name: Spearmanr
---

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# bert_tiny_olda_book_5_v1_stsb

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_olda_book_5_v1](https://huggingface.co/gokulsrinivasagan/bert_tiny_olda_book_5_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0791
- Pearson: 0.3873
- Spearmanr: 0.3909
- Combined Score: 0.3891

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 6.666         | 1.0   | 23   | 3.1262          | 0.0081  | 0.0056    | 0.0069         |
| 2.4779        | 2.0   | 46   | 2.6620          | 0.0570  | -0.0124   | 0.0223         |
| 2.1647        | 3.0   | 69   | 2.2854          | 0.1253  | 0.1253    | 0.1253         |
| 2.0395        | 4.0   | 92   | 2.3712          | 0.1357  | 0.1386    | 0.1371         |
| 1.8801        | 5.0   | 115  | 2.3718          | 0.1949  | 0.1957    | 0.1953         |
| 1.74          | 6.0   | 138  | 2.2306          | 0.2877  | 0.2822    | 0.2850         |
| 1.5258        | 7.0   | 161  | 2.2584          | 0.3352  | 0.3433    | 0.3392         |
| 1.3517        | 8.0   | 184  | 2.1435          | 0.3680  | 0.3726    | 0.3703         |
| 1.173         | 9.0   | 207  | 2.0791          | 0.3873  | 0.3909    | 0.3891         |
| 1.0636        | 10.0  | 230  | 2.1585          | 0.3870  | 0.3912    | 0.3891         |
| 0.9475        | 11.0  | 253  | 2.5705          | 0.3772  | 0.3945    | 0.3859         |
| 0.8403        | 12.0  | 276  | 2.1378          | 0.4000  | 0.4003    | 0.4002         |
| 0.7236        | 13.0  | 299  | 2.3459          | 0.3771  | 0.3813    | 0.3792         |
| 0.688         | 14.0  | 322  | 2.2095          | 0.4002  | 0.4023    | 0.4013         |


### Framework versions

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