---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- gokulsrinivasagan/processed_book_corpus-ld-5
metrics:
- accuracy
model-index:
- name: bert_tiny_lda_5_v1_book
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: gokulsrinivasagan/processed_book_corpus-ld-5
      type: gokulsrinivasagan/processed_book_corpus-ld-5
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6857676426031905
---

<!-- 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. -->

# bert_tiny_lda_5_v1_book

This model is a fine-tuned version of [](https://huggingface.co/) on the gokulsrinivasagan/processed_book_corpus-ld-5 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8600
- Accuracy: 0.6858

## 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: 0.0001
- train_batch_size: 160
- eval_batch_size: 160
- 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
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25

### Training results

| Training Loss | Epoch   | Step   | Validation Loss | Accuracy |
|:-------------:|:-------:|:------:|:---------------:|:--------:|
| 7.2508        | 0.7025  | 10000  | 7.0913          | 0.1639   |
| 5.6868        | 1.4051  | 20000  | 5.0071          | 0.4074   |
| 4.0487        | 2.1076  | 30000  | 3.6967          | 0.5617   |
| 3.7657        | 2.8102  | 40000  | 3.4422          | 0.5989   |
| 3.6336        | 3.5127  | 50000  | 3.3142          | 0.6176   |
| 3.5449        | 4.2153  | 60000  | 3.2372          | 0.6291   |
| 3.4893        | 4.9178  | 70000  | 3.1788          | 0.6376   |
| 3.4397        | 5.6203  | 80000  | 3.1367          | 0.6442   |
| 3.4066        | 6.3229  | 90000  | 3.1054          | 0.6491   |
| 3.3758        | 7.0254  | 100000 | 3.0734          | 0.6534   |
| 3.3548        | 7.7280  | 110000 | 3.0504          | 0.6571   |
| 3.3302        | 8.4305  | 120000 | 3.0304          | 0.6599   |
| 3.3087        | 9.1331  | 130000 | 3.0157          | 0.6620   |
| 3.2942        | 9.8356  | 140000 | 2.9982          | 0.6654   |
| 3.2799        | 10.5381 | 150000 | 2.9831          | 0.6672   |
| 3.271         | 11.2407 | 160000 | 2.9750          | 0.6687   |
| 3.2545        | 11.9432 | 170000 | 2.9624          | 0.6703   |
| 3.2444        | 12.6458 | 180000 | 2.9493          | 0.6723   |
| 3.2336        | 13.3483 | 190000 | 2.9428          | 0.6731   |
| 3.2254        | 14.0509 | 200000 | 2.9316          | 0.6746   |
| 3.2143        | 14.7534 | 210000 | 2.9231          | 0.6759   |
| 3.2058        | 15.4560 | 220000 | 2.9154          | 0.6772   |
| 3.2014        | 16.1585 | 230000 | 2.9095          | 0.6780   |
| 3.1923        | 16.8610 | 240000 | 2.9047          | 0.6788   |
| 3.1846        | 17.5636 | 250000 | 2.8982          | 0.6797   |
| 3.1797        | 18.2661 | 260000 | 2.8922          | 0.6805   |
| 3.1768        | 18.9687 | 270000 | 2.8886          | 0.6813   |
| 3.1696        | 19.6712 | 280000 | 2.8828          | 0.6822   |
| 3.1656        | 20.3738 | 290000 | 2.8787          | 0.6826   |
| 3.1581        | 21.0763 | 300000 | 2.8756          | 0.6834   |
| 3.1566        | 21.7788 | 310000 | 2.8690          | 0.6842   |
| 3.1508        | 22.4814 | 320000 | 2.8671          | 0.6845   |
| 3.1496        | 23.1839 | 330000 | 2.8648          | 0.6849   |
| 3.1475        | 23.8865 | 340000 | 2.8612          | 0.6853   |
| 3.1459        | 24.5890 | 350000 | 2.8586          | 0.6859   |


### Framework versions

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