transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/distilbert_base_lda_train_book base_model:finetune:gokulsrinivasagan/distilbert_base_lda_train_book license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/distilbert_base_lda_train_book
datasets:
- glue
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: distilbert_base_lda_train_book_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.830696828989416
      name: Spearmanr
---

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# distilbert_base_lda_train_book_stsb

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_base_lda_train_book](https://huggingface.co/gokulsrinivasagan/distilbert_base_lda_train_book) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7113
- Pearson: 0.8296
- Spearmanr: 0.8307
- Combined Score: 0.8302

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.0194        | 1.0   | 23   | 2.4197          | 0.2062  | 0.1864    | 0.1963         |
| 1.598         | 2.0   | 46   | 1.5087          | 0.6707  | 0.6808    | 0.6758         |
| 0.9326        | 3.0   | 69   | 1.0089          | 0.7648  | 0.7720    | 0.7684         |
| 0.8373        | 4.0   | 92   | 1.1543          | 0.7738  | 0.7886    | 0.7812         |
| 0.6773        | 5.0   | 115  | 1.3859          | 0.7765  | 0.8013    | 0.7889         |
| 0.5298        | 6.0   | 138  | 1.5307          | 0.7855  | 0.8085    | 0.7970         |
| 0.4235        | 7.0   | 161  | 0.7789          | 0.8101  | 0.8107    | 0.8104         |
| 0.3212        | 8.0   | 184  | 0.7200          | 0.8249  | 0.8234    | 0.8241         |
| 0.2905        | 9.0   | 207  | 1.1265          | 0.8156  | 0.8184    | 0.8170         |
| 0.2275        | 10.0  | 230  | 0.9589          | 0.8095  | 0.8134    | 0.8114         |
| 0.209         | 11.0  | 253  | 0.8233          | 0.8253  | 0.8269    | 0.8261         |
| 0.172         | 12.0  | 276  | 0.7129          | 0.8335  | 0.8325    | 0.8330         |
| 0.1582        | 13.0  | 299  | 0.7131          | 0.8286  | 0.8287    | 0.8286         |
| 0.1383        | 14.0  | 322  | 0.8368          | 0.8259  | 0.8290    | 0.8275         |
| 0.1278        | 15.0  | 345  | 0.8243          | 0.8309  | 0.8310    | 0.8309         |
| 0.1053        | 16.0  | 368  | 0.7220          | 0.8323  | 0.8299    | 0.8311         |
| 0.1123        | 17.0  | 391  | 0.7113          | 0.8296  | 0.8307    | 0.8302         |
| 0.128         | 18.0  | 414  | 0.8336          | 0.8268  | 0.8320    | 0.8294         |
| 0.1053        | 19.0  | 437  | 0.9353          | 0.8230  | 0.8293    | 0.8262         |
| 0.0923        | 20.0  | 460  | 0.9611          | 0.8266  | 0.8330    | 0.8298         |
| 0.0882        | 21.0  | 483  | 0.7890          | 0.8304  | 0.8333    | 0.8319         |
| 0.0813        | 22.0  | 506  | 0.9056          | 0.8230  | 0.8273    | 0.8252         |


### Framework versions

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