transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_base_lda_100_v1 base_model:finetune:gokulsrinivasagan/bert_base_lda_100_v1 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_base_lda_100_v1
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: bert_base_lda_100_v1_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.5325439607950028
      name: Spearmanr
---

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# bert_base_lda_100_v1_stsb

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_100_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6844
- Pearson: 0.5330
- Spearmanr: 0.5325
- Combined Score: 0.5328

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.7331        | 1.0   | 23   | 2.6189          | 0.0643  | 0.0760    | 0.0701         |
| 1.9804        | 2.0   | 46   | 2.0897          | 0.2818  | 0.2688    | 0.2753         |
| 1.7486        | 3.0   | 69   | 1.9471          | 0.4158  | 0.4153    | 0.4155         |
| 1.2963        | 4.0   | 92   | 2.3058          | 0.4520  | 0.4674    | 0.4597         |
| 1.0162        | 5.0   | 115  | 1.8442          | 0.4887  | 0.4888    | 0.4888         |
| 0.8446        | 6.0   | 138  | 1.7664          | 0.5228  | 0.5290    | 0.5259         |
| 0.6767        | 7.0   | 161  | 1.7574          | 0.5152  | 0.5185    | 0.5168         |
| 0.5349        | 8.0   | 184  | 1.6844          | 0.5330  | 0.5325    | 0.5328         |
| 0.4606        | 9.0   | 207  | 1.9862          | 0.5039  | 0.5084    | 0.5062         |
| 0.3951        | 10.0  | 230  | 1.8024          | 0.5266  | 0.5275    | 0.5270         |
| 0.3624        | 11.0  | 253  | 2.0157          | 0.5342  | 0.5423    | 0.5382         |
| 0.3087        | 12.0  | 276  | 2.4094          | 0.5227  | 0.5385    | 0.5306         |
| 0.2879        | 13.0  | 299  | 2.0560          | 0.5304  | 0.5350    | 0.5327         |


### Framework versions

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