metadata
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
datasets:
- gokuls/wiki_book_corpus_complete_processed_bert_dataset
metrics:
- accuracy
model-index:
- name: BERT_pretraining_h_100_wo_deepspeed
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: 0.15387755648267093
BERT_pretraining_h_100_wo_deepspeed
This model is a fine-tuned version of bert-large-uncased on the gokuls/wiki_book_corpus_complete_processed_bert_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 5.7778
- Accuracy: 0.1539
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: 208
- eval_batch_size: 208
- seed: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100000
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.8769 | 0.36 | 10000 | 6.7582 | 0.1101 |
| 6.4647 | 0.71 | 20000 | 6.4764 | 0.1314 |
| 6.3679 | 1.07 | 30000 | 6.3218 | 0.1407 |
| 6.252 | 1.42 | 40000 | 6.2139 | 0.1454 |
| 6.2132 | 1.78 | 50000 | 6.1398 | 0.1478 |
| 6.0407 | 2.13 | 60000 | 6.0774 | 0.1502 |
| 6.0694 | 2.49 | 70000 | 6.0303 | 0.1516 |
| 5.9996 | 2.84 | 80000 | 5.9893 | 0.1521 |
| 5.9166 | 3.2 | 90000 | 5.9553 | 0.1526 |
| 5.8915 | 3.55 | 100000 | 5.9261 | 0.1530 |
| 5.8924 | 3.91 | 110000 | 5.8996 | 0.1534 |
| 5.8972 | 4.26 | 120000 | 5.8814 | 0.1533 |
| 5.8454 | 4.62 | 130000 | 5.8626 | 0.1532 |
| 5.8104 | 4.97 | 140000 | 5.8494 | 0.1534 |
| 5.8461 | 5.33 | 150000 | 5.8378 | 0.1534 |
| 5.8476 | 5.68 | 160000 | 5.8246 | 0.1536 |
| 5.7255 | 6.04 | 170000 | 5.8155 | 0.1532 |
| 5.8431 | 6.39 | 180000 | 5.8068 | 0.1537 |
| 5.7526 | 6.75 | 190000 | 5.7981 | 0.1537 |
| 5.7826 | 7.1 | 200000 | 5.7886 | 0.1537 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1