---
tags:
- generated_from_trainer
datasets:
- gokuls/wiki_book_corpus_complete_processed_bert_dataset
metrics:
- accuracy
model-index:
- name: HBERTv1_emb_compress_48_L10_H256_A4
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: gokuls/wiki_book_corpus_complete_processed_bert_dataset
      type: gokuls/wiki_book_corpus_complete_processed_bert_dataset
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.15093352306316574
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# HBERTv1_emb_compress_48_L10_H256_A4

This model is a fine-tuned version of [](https://huggingface.co/) on the gokuls/wiki_book_corpus_complete_processed_bert_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 6.0495
- Accuracy: 0.1509

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 7.1164        | 0.11  | 10000  | 7.0967          | 0.0830   |
| 6.694         | 0.22  | 20000  | 6.6867          | 0.1065   |
| 6.545         | 0.33  | 30000  | 6.5445          | 0.1171   |
| 6.4556        | 0.44  | 40000  | 6.4527          | 0.1250   |
| 6.3891        | 0.55  | 50000  | 6.3831          | 0.1305   |
| 6.3404        | 0.66  | 60000  | 6.3334          | 0.1350   |
| 6.2962        | 0.76  | 70000  | 6.2940          | 0.1377   |
| 6.2669        | 0.87  | 80000  | 6.2629          | 0.1398   |
| 6.2352        | 0.98  | 90000  | 6.2361          | 0.1412   |
| 6.2179        | 1.09  | 100000 | 6.2150          | 0.1429   |
| 6.191         | 1.2   | 110000 | 6.1970          | 0.1443   |
| 6.1809        | 1.31  | 120000 | 6.1829          | 0.1441   |
| 6.1699        | 1.42  | 130000 | 6.1692          | 0.1455   |
| 6.1623        | 1.53  | 140000 | 6.1562          | 0.1453   |
| 6.1422        | 1.64  | 150000 | 6.1480          | 0.1468   |
| 6.1397        | 1.75  | 160000 | 6.1367          | 0.1468   |
| 6.1342        | 1.86  | 170000 | 6.1284          | 0.1475   |
| 6.1291        | 1.97  | 180000 | 6.1214          | 0.1478   |
| 6.1157        | 2.08  | 190000 | 6.1132          | 0.1483   |
| 6.1146        | 2.18  | 200000 | 6.1094          | 0.1484   |
| 6.1018        | 2.29  | 210000 | 6.1013          | 0.1488   |
| 6.1014        | 2.4   | 220000 | 6.0979          | 0.1488   |
| 6.0935        | 2.51  | 230000 | 6.0936          | 0.1489   |
| 6.0899        | 2.62  | 240000 | 6.0881          | 0.1491   |
| 6.0858        | 2.73  | 250000 | 6.0851          | 0.1498   |
| 6.0872        | 2.84  | 260000 | 6.0819          | 0.1497   |
| 6.0858        | 2.95  | 270000 | 6.0784          | 0.1500   |
| 6.0775        | 3.06  | 280000 | 6.0745          | 0.1501   |
| 6.0715        | 3.17  | 290000 | 6.0720          | 0.1502   |
| 6.0704        | 3.28  | 300000 | 6.0699          | 0.1502   |
| 6.0678        | 3.39  | 310000 | 6.0668          | 0.1503   |
| 6.0662        | 3.5   | 320000 | 6.0649          | 0.1503   |
| 6.0569        | 3.6   | 330000 | 6.0622          | 0.1505   |
| 6.0604        | 3.71  | 340000 | 6.0612          | 0.1506   |
| 6.0525        | 3.82  | 350000 | 6.0586          | 0.1507   |
| 6.0553        | 3.93  | 360000 | 6.0582          | 0.1506   |
| 6.053         | 4.04  | 370000 | 6.0544          | 0.1508   |
| 6.0594        | 4.15  | 380000 | 6.0553          | 0.1507   |
| 6.0488        | 4.26  | 390000 | 6.0527          | 0.1509   |
| 6.051         | 4.37  | 400000 | 6.0516          | 0.1509   |
| 6.0553        | 4.48  | 410000 | 6.0518          | 0.1509   |
| 6.0507        | 4.59  | 420000 | 6.0520          | 0.1509   |
| 6.0514        | 4.7   | 430000 | 6.0501          | 0.1509   |
| 6.0511        | 4.81  | 440000 | 6.0496          | 0.1511   |
| 6.0527        | 4.92  | 450000 | 6.0493          | 0.1509   |


### Framework versions

- Transformers 4.33.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.13.3