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README.md
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---
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license: apache-2.0
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base_model: bert-base-uncased
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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_sst2_padding70model
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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_sst2_padding70model
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6816
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- Accuracy: 0.9209
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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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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- num_epochs: 20
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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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| No log | 1.0 | 433 | 0.2422 | 0.9121 |
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| 0.3225 | 2.0 | 866 | 0.3330 | 0.9094 |
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| 0.15 | 3.0 | 1299 | 0.4125 | 0.9193 |
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| 0.0796 | 4.0 | 1732 | 0.4849 | 0.9088 |
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| 0.033 | 5.0 | 2165 | 0.6146 | 0.9023 |
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| 0.0252 | 6.0 | 2598 | 0.5862 | 0.9105 |
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| 0.0147 | 7.0 | 3031 | 0.6562 | 0.9121 |
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| 0.0147 | 8.0 | 3464 | 0.6735 | 0.9171 |
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| 0.01 | 9.0 | 3897 | 0.7122 | 0.9099 |
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| 0.017 | 10.0 | 4330 | 0.6584 | 0.9149 |
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| 0.0106 | 11.0 | 4763 | 0.7113 | 0.9171 |
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| 0.0077 | 12.0 | 5196 | 0.7330 | 0.9149 |
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| 0.0108 | 13.0 | 5629 | 0.6942 | 0.9143 |
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| 0.0126 | 14.0 | 6062 | 0.6131 | 0.9160 |
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| 0.0126 | 15.0 | 6495 | 0.6609 | 0.9182 |
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| 0.0074 | 16.0 | 6928 | 0.6579 | 0.9193 |
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| 0.0075 | 17.0 | 7361 | 0.6388 | 0.9220 |
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| 0.002 | 18.0 | 7794 | 0.6524 | 0.9253 |
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| 0.0014 | 19.0 | 8227 | 0.6741 | 0.9209 |
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| 0.0009 | 20.0 | 8660 | 0.6816 | 0.9209 |
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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