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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: add_bert_12_layer_model_complete_training_new_96
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results: []
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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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# add_bert_12_layer_model_complete_training_new_96
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This model is a fine-tuned version of [gokuls/add_bert_12_layer_model_complete_training_new_48](https://huggingface.co/gokuls/add_bert_12_layer_model_complete_training_new_48) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 5.4112
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- Accuracy: 0.1893
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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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| 5.8144 | 0.08 | 10000 | 5.7474 | 0.1593 |
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| 5.7889 | 0.16 | 20000 | 5.7204 | 0.1604 |
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| 5.6347 | 0.25 | 30000 | 5.6966 | 0.1623 |
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| 5.7138 | 0.33 | 40000 | 5.6725 | 0.1636 |
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| 5.6769 | 0.41 | 50000 | 5.6518 | 0.1658 |
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| 5.6603 | 0.49 | 60000 | 5.6290 | 0.1686 |
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| 5.5852 | 0.57 | 70000 | 5.6076 | 0.1707 |
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| 5.6607 | 0.66 | 80000 | 5.5906 | 0.1720 |
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| 5.5823 | 0.74 | 90000 | 5.5719 | 0.1739 |
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| 5.6124 | 0.82 | 100000 | 5.5543 | 0.1759 |
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| 5.6478 | 0.9 | 110000 | 5.5358 | 0.1776 |
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| 5.4795 | 0.98 | 120000 | 5.5203 | 0.1787 |
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| 5.4557 | 1.07 | 130000 | 5.5028 | 0.1804 |
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| 5.5585 | 1.15 | 140000 | 5.4923 | 0.1814 |
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| 5.6387 | 1.23 | 150000 | 5.4781 | 0.1825 |
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| 5.479 | 1.31 | 160000 | 5.4663 | 0.1833 |
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| 5.3951 | 1.39 | 170000 | 5.4512 | 0.1851 |
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| 5.5062 | 1.47 | 180000 | 5.4411 | 0.1864 |
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| 5.4553 | 1.56 | 190000 | 5.4244 | 0.1881 |
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| 5.5461 | 1.64 | 200000 | 5.4112 | 0.1893 |
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### Framework versions
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- Transformers 4.30.1
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- Pytorch 1.14.0a0+410ce96
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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