transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_base_lda_5_v1_book base_model:finetune:gokulsrinivasagan/bert_base_lda_5_v1_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_base_lda_5_v1_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: bert_base_lda_5_v1_book_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.787735482912616
      name: Spearmanr
---

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# bert_base_lda_5_v1_book_stsb

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_5_v1_book](https://huggingface.co/gokulsrinivasagan/bert_base_lda_5_v1_book) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8673
- Pearson: 0.7861
- Spearmanr: 0.7877
- Combined Score: 0.7869

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.7484        | 1.0   | 23   | 2.4116          | 0.1017  | 0.1088    | 0.1053         |
| 1.8536        | 2.0   | 46   | 1.8544          | 0.4512  | 0.4690    | 0.4601         |
| 1.1916        | 3.0   | 69   | 1.4727          | 0.7543  | 0.7787    | 0.7665         |
| 0.7783        | 4.0   | 92   | 0.8673          | 0.7861  | 0.7877    | 0.7869         |
| 0.6111        | 5.0   | 115  | 0.9008          | 0.7971  | 0.8020    | 0.7995         |
| 0.4555        | 6.0   | 138  | 0.8735          | 0.8045  | 0.8095    | 0.8070         |
| 0.3315        | 7.0   | 161  | 1.0318          | 0.7981  | 0.8094    | 0.8037         |
| 0.2701        | 8.0   | 184  | 0.9214          | 0.8062  | 0.8126    | 0.8094         |
| 0.2298        | 9.0   | 207  | 0.9049          | 0.8019  | 0.8090    | 0.8054         |


### Framework versions

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