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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: bert_12_layer_model_v2_complete_training_new_120
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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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# bert_12_layer_model_v2_complete_training_new_120
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_96](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_96) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.4439
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- Accuracy: 0.5517
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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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| 2.7038 | 0.08 | 10000 | 2.6207 | 0.5282 |
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| 2.6766 | 0.16 | 20000 | 2.5968 | 0.5309 |
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| 2.6536 | 0.25 | 30000 | 2.5717 | 0.5346 |
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| 2.645 | 0.33 | 40000 | 2.5576 | 0.5365 |
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| 2.6164 | 0.41 | 50000 | 2.5344 | 0.5396 |
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| 2.6027 | 0.49 | 60000 | 2.5164 | 0.5419 |
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| 2.5779 | 0.57 | 70000 | 2.5001 | 0.5443 |
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| 2.5642 | 0.66 | 80000 | 2.4863 | 0.5460 |
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| 2.5439 | 0.74 | 90000 | 2.4716 | 0.5476 |
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| 2.5344 | 0.82 | 100000 | 2.4551 | 0.5502 |
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| 2.5314 | 0.9 | 110000 | 2.4439 | 0.5517 |
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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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