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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: HBERTv1_emb_compress_48_L12_H64_A2 |
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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: 0.12850906143802152 |
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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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# HBERTv1_emb_compress_48_L12_H64_A2 |
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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: 6.4079 |
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- Accuracy: 0.1285 |
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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: 96 |
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- eval_batch_size: 96 |
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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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| 8.6554 | 0.16 | 10000 | 8.5846 | 0.0483 | |
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| 7.2331 | 0.33 | 20000 | 7.2280 | 0.0542 | |
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| 7.0014 | 0.49 | 30000 | 6.9927 | 0.0677 | |
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| 6.8699 | 0.66 | 40000 | 6.8637 | 0.0856 | |
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| 6.7777 | 0.82 | 50000 | 6.7726 | 0.0922 | |
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| 6.7091 | 0.98 | 60000 | 6.7101 | 0.0974 | |
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| 6.6626 | 1.15 | 70000 | 6.6620 | 0.1015 | |
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| 6.6279 | 1.31 | 80000 | 6.6255 | 0.1040 | |
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| 6.5917 | 1.47 | 90000 | 6.5948 | 0.1068 | |
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| 6.5691 | 1.64 | 100000 | 6.5695 | 0.1094 | |
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| 6.5486 | 1.8 | 110000 | 6.5460 | 0.1122 | |
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| 6.5246 | 1.97 | 120000 | 6.5275 | 0.1144 | |
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| 6.5069 | 2.13 | 130000 | 6.5115 | 0.1162 | |
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| 6.5001 | 2.29 | 140000 | 6.4962 | 0.1180 | |
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| 6.4785 | 2.46 | 150000 | 6.4822 | 0.1197 | |
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| 6.4706 | 2.62 | 160000 | 6.4714 | 0.1212 | |
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| 6.4612 | 2.79 | 170000 | 6.4610 | 0.1225 | |
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| 6.4485 | 2.95 | 180000 | 6.4530 | 0.1233 | |
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| 6.4477 | 3.11 | 190000 | 6.4441 | 0.1243 | |
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| 6.4373 | 3.28 | 200000 | 6.4395 | 0.1251 | |
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| 6.4351 | 3.44 | 210000 | 6.4322 | 0.1259 | |
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| 6.4273 | 3.6 | 220000 | 6.4264 | 0.1262 | |
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| 6.4153 | 3.77 | 230000 | 6.4219 | 0.1269 | |
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| 6.4188 | 3.93 | 240000 | 6.4182 | 0.1274 | |
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| 6.4128 | 4.1 | 250000 | 6.4150 | 0.1278 | |
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| 6.4189 | 4.26 | 260000 | 6.4121 | 0.1280 | |
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| 6.4102 | 4.42 | 270000 | 6.4112 | 0.1282 | |
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| 6.4105 | 4.59 | 280000 | 6.4087 | 0.1285 | |
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| 6.4065 | 4.75 | 290000 | 6.4067 | 0.1287 | |
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| 6.4082 | 4.92 | 300000 | 6.4070 | 0.1285 | |
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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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