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--- |
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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_12_layer_model_v3_complete_training_new_emb_compress_48 |
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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: 0.1573752894874488 |
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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_12_layer_model_v3_complete_training_new_emb_compress_48 |
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This model is a fine-tuned version of [](https://huggingface.co/) 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: 5.9594 |
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- Accuracy: 0.1574 |
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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: 1e-05 |
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- train_batch_size: 48 |
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- eval_batch_size: 48 |
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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: 10000 |
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- num_epochs: 5 |
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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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| 7.1148 | 0.08 | 10000 | 7.0921 | 0.0828 | |
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| 6.6864 | 0.16 | 20000 | 6.6879 | 0.1078 | |
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| 6.5451 | 0.25 | 30000 | 6.5435 | 0.1184 | |
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| 6.4606 | 0.33 | 40000 | 6.4515 | 0.1262 | |
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| 6.3851 | 0.41 | 50000 | 6.3851 | 0.1312 | |
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| 6.3371 | 0.49 | 60000 | 6.3357 | 0.1342 | |
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| 6.2971 | 0.57 | 70000 | 6.2923 | 0.1373 | |
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| 6.2682 | 0.66 | 80000 | 6.2605 | 0.1399 | |
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| 6.2352 | 0.74 | 90000 | 6.2301 | 0.1411 | |
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| 6.214 | 0.82 | 100000 | 6.2090 | 0.1430 | |
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| 6.1837 | 0.9 | 110000 | 6.1865 | 0.1443 | |
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| 6.1726 | 0.98 | 120000 | 6.1682 | 0.1451 | |
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| 6.1524 | 1.07 | 130000 | 6.1498 | 0.1464 | |
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| 6.1293 | 1.15 | 140000 | 6.1300 | 0.1468 | |
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| 6.1116 | 1.23 | 150000 | 6.1026 | 0.1479 | |
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| 6.0839 | 1.31 | 160000 | 6.0797 | 0.1490 | |
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| 6.0616 | 1.39 | 170000 | 6.0590 | 0.1499 | |
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| 6.0508 | 1.47 | 180000 | 6.0399 | 0.1509 | |
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| 6.0311 | 1.56 | 190000 | 6.0233 | 0.1517 | |
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| 6.015 | 1.64 | 200000 | 6.0048 | 0.1533 | |
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| 5.985 | 1.72 | 210000 | 5.9863 | 0.1547 | |
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| 5.9661 | 1.8 | 220000 | 5.9595 | 0.1573 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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