transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_tiny_lda_100_v1 base_model:finetune:gokulsrinivasagan/bert_tiny_lda_100_v1 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_tiny_lda_100_v1
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_lda_100_v1_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.22878969383272044
      name: Spearmanr
---

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# bert_tiny_lda_100_v1_stsb

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3632
- Pearson: 0.2350
- Spearmanr: 0.2288
- Combined Score: 0.2319

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.8077        | 1.0   | 23   | 2.3850          | 0.0667  | 0.0654    | 0.0661         |
| 2.042         | 2.0   | 46   | 2.6089          | 0.0834  | 0.0848    | 0.0841         |
| 1.9254        | 3.0   | 69   | 2.3926          | 0.1539  | 0.1394    | 0.1466         |
| 1.8381        | 4.0   | 92   | 2.5560          | 0.1744  | 0.1720    | 0.1732         |
| 1.6974        | 5.0   | 115  | 3.0257          | 0.1812  | 0.1757    | 0.1784         |
| 1.5776        | 6.0   | 138  | 2.3632          | 0.2350  | 0.2288    | 0.2319         |
| 1.2951        | 7.0   | 161  | 2.4535          | 0.2594  | 0.2573    | 0.2584         |
| 1.0896        | 8.0   | 184  | 2.5246          | 0.2652  | 0.2622    | 0.2637         |
| 0.9372        | 9.0   | 207  | 2.9827          | 0.2716  | 0.2570    | 0.2643         |
| 0.7915        | 10.0  | 230  | 2.6918          | 0.3056  | 0.2926    | 0.2991         |
| 0.673         | 11.0  | 253  | 2.7520          | 0.3013  | 0.2887    | 0.2950         |


### Framework versions

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