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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: sa_bert_12_layer_modified_complete_training_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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# sa_bert_12_layer_modified_complete_training_96
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This model is a fine-tuned version of [gokuls/sa_bert_12_layer_modified_complete_training_72_v2](https://huggingface.co/gokuls/sa_bert_12_layer_modified_complete_training_72_v2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5432
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- Accuracy: 0.5446
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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: 32
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- eval_batch_size: 32
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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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| 2.9291 | 0.05 | 10000 | 2.7772 | 0.5161 |
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| 2.8002 | 0.11 | 20000 | 2.7374 | 0.5210 |
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| 2.6962 | 0.16 | 30000 | 2.6995 | 0.5256 |
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| 2.6628 | 0.22 | 40000 | 2.6681 | 0.5296 |
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| 2.7735 | 0.27 | 50000 | 2.6399 | 0.5332 |
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| 2.6821 | 0.33 | 60000 | 2.6079 | 0.5366 |
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| 2.6073 | 0.38 | 70000 | 2.5830 | 0.5397 |
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| 2.6742 | 0.44 | 80000 | 2.5624 | 0.5422 |
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| 2.8162 | 0.49 | 90000 | 2.5432 | 0.5446 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 1.14.0a0+410ce96
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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