transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/distilbert_lda_50_v1 base_model:finetune:gokulsrinivasagan/distilbert_lda_50_v1 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/distilbert_lda_50_v1
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: distilbert_lda_50_v1_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.6483204508628595
      name: Spearmanr
---

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# distilbert_lda_50_v1_stsb

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_50_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_50_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3807
- Pearson: 0.6576
- Spearmanr: 0.6483
- Combined Score: 0.6529

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.6455        | 1.0   | 23   | 2.4817          | 0.0933  | 0.0791    | 0.0862         |
| 2.0015        | 2.0   | 46   | 2.5968          | 0.1340  | 0.1191    | 0.1265         |
| 1.875         | 3.0   | 69   | 2.2990          | 0.2213  | 0.2184    | 0.2198         |
| 1.4576        | 4.0   | 92   | 2.3398          | 0.4446  | 0.4147    | 0.4296         |
| 1.0618        | 5.0   | 115  | 1.8954          | 0.5425  | 0.5250    | 0.5338         |
| 0.7001        | 6.0   | 138  | 1.9422          | 0.5693  | 0.5653    | 0.5673         |
| 0.5415        | 7.0   | 161  | 2.0586          | 0.5778  | 0.5692    | 0.5735         |
| 0.4005        | 8.0   | 184  | 1.5390          | 0.6166  | 0.6056    | 0.6111         |
| 0.3147        | 9.0   | 207  | 1.7006          | 0.5953  | 0.5793    | 0.5873         |
| 0.2829        | 10.0  | 230  | 1.4072          | 0.6480  | 0.6375    | 0.6428         |
| 0.2308        | 11.0  | 253  | 1.5357          | 0.6279  | 0.6134    | 0.6207         |
| 0.1996        | 12.0  | 276  | 1.6600          | 0.6341  | 0.6212    | 0.6276         |
| 0.1822        | 13.0  | 299  | 1.5625          | 0.6463  | 0.6354    | 0.6409         |
| 0.1646        | 14.0  | 322  | 1.3891          | 0.6635  | 0.6566    | 0.6601         |
| 0.1492        | 15.0  | 345  | 1.3807          | 0.6576  | 0.6483    | 0.6529         |
| 0.1296        | 16.0  | 368  | 1.4665          | 0.6426  | 0.6319    | 0.6372         |
| 0.1306        | 17.0  | 391  | 1.5261          | 0.6364  | 0.6213    | 0.6288         |
| 0.1205        | 18.0  | 414  | 1.4115          | 0.6427  | 0.6266    | 0.6347         |
| 0.1087        | 19.0  | 437  | 1.5183          | 0.6400  | 0.6248    | 0.6324         |
| 0.1072        | 20.0  | 460  | 1.5816          | 0.6414  | 0.6310    | 0.6362         |


### Framework versions

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