transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/distilbert_lda_100_v1 base_model:finetune:gokulsrinivasagan/distilbert_lda_100_v1 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/distilbert_lda_100_v1
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: distilbert_lda_100_v1_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.7703935491023064
      name: Spearmanr
---

<!-- 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. -->

# distilbert_lda_100_v1_stsb

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_100_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_100_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9153
- Pearson: 0.7758
- Spearmanr: 0.7704
- Combined Score: 0.7731

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.622         | 1.0   | 23   | 2.5298          | 0.1011  | 0.0891    | 0.0951         |
| 1.8404        | 2.0   | 46   | 2.3343          | 0.4642  | 0.4648    | 0.4645         |
| 1.3143        | 3.0   | 69   | 1.2509          | 0.6736  | 0.6670    | 0.6703         |
| 0.8809        | 4.0   | 92   | 1.3874          | 0.7172  | 0.7254    | 0.7213         |
| 0.6317        | 5.0   | 115  | 1.5835          | 0.7091  | 0.7238    | 0.7164         |
| 0.5139        | 6.0   | 138  | 1.2793          | 0.7443  | 0.7470    | 0.7456         |
| 0.3919        | 7.0   | 161  | 1.0238          | 0.7576  | 0.7535    | 0.7556         |
| 0.3125        | 8.0   | 184  | 1.4519          | 0.7331  | 0.7349    | 0.7340         |
| 0.281         | 9.0   | 207  | 1.2564          | 0.7390  | 0.7374    | 0.7382         |
| 0.2395        | 10.0  | 230  | 0.9153          | 0.7758  | 0.7704    | 0.7731         |
| 0.2219        | 11.0  | 253  | 1.2411          | 0.7509  | 0.7509    | 0.7509         |
| 0.1923        | 12.0  | 276  | 1.5144          | 0.7429  | 0.7444    | 0.7436         |
| 0.1688        | 13.0  | 299  | 1.0667          | 0.7518  | 0.7468    | 0.7493         |
| 0.1494        | 14.0  | 322  | 1.2371          | 0.7502  | 0.7483    | 0.7493         |
| 0.1498        | 15.0  | 345  | 1.1066          | 0.7473  | 0.7433    | 0.7453         |


### Framework versions

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