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--- |
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license: apache-2.0 |
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base_model: bert-large-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- gokuls/wiki_book_corpus_complete_processed_bert_dataset |
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metrics: |
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- accuracy |
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model-index: |
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- name: BERT_pretraining_h_100 |
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results: |
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- task: |
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name: Masked Language Modeling |
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type: fill-mask |
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dataset: |
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name: gokuls/wiki_book_corpus_complete_processed_bert_dataset |
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type: gokuls/wiki_book_corpus_complete_processed_bert_dataset |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.046532742314357264 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# BERT_pretraining_h_100 |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the gokuls/wiki_book_corpus_complete_processed_bert_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 7.2715 |
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- Accuracy: 0.0465 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 36 |
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- eval_batch_size: 36 |
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- seed: 10 |
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- distributed_type: multi-GPU |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100000 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:------:|:---------------:|:--------:| |
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| 6.5136 | 0.06 | 10000 | 6.4841 | 0.1332 | |
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| 6.3225 | 0.12 | 20000 | 6.2865 | 0.1452 | |
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| 6.0806 | 0.18 | 30000 | 6.1945 | 0.1482 | |
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| 6.1449 | 0.25 | 40000 | 6.1284 | 0.1497 | |
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| 5.7325 | 0.31 | 50000 | 5.8403 | 0.1609 | |
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| 4.0177 | 0.37 | 60000 | 3.7789 | 0.3887 | |
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| 3.3942 | 0.43 | 70000 | 3.1742 | 0.4638 | |
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| 3.2801 | 0.49 | 80000 | 3.0618 | 0.4775 | |
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| 7.2562 | 0.55 | 90000 | 7.2798 | 0.0432 | |
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| 7.226 | 0.61 | 100000 | 7.2771 | 0.0465 | |
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| 7.2174 | 0.68 | 110000 | 7.2764 | 0.0465 | |
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| 7.232 | 0.74 | 120000 | 7.2745 | 0.0465 | |
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| 7.2003 | 0.8 | 130000 | 7.2730 | 0.0465 | |
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| 7.0964 | 0.86 | 140000 | 7.2725 | 0.0466 | |
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| 7.5174 | 0.92 | 150000 | 7.2729 | 0.0465 | |
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| 7.2674 | 0.98 | 160000 | 7.2729 | 0.0465 | |
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| 7.2044 | 1.04 | 170000 | 7.2729 | 0.0466 | |
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### Framework versions |
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- Transformers 4.37.1 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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