End of training
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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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datasets:
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- imdb
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metrics:
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- accuracy
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model-index:
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- name: N_bert_imdb_padding20model
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: imdb
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type: imdb
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config: plain_text
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split: test
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args: plain_text
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.94048
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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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# N_bert_imdb_padding20model
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6296
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- Accuracy: 0.9405
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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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| 0.2224 | 1.0 | 1563 | 0.2481 | 0.9156 |
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| 0.1564 | 2.0 | 3126 | 0.2097 | 0.9386 |
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| 0.0937 | 3.0 | 4689 | 0.2687 | 0.9347 |
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| 0.056 | 4.0 | 6252 | 0.2934 | 0.9377 |
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| 0.0382 | 5.0 | 7815 | 0.3589 | 0.9370 |
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| 0.0304 | 6.0 | 9378 | 0.4149 | 0.9355 |
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| 0.02 | 7.0 | 10941 | 0.4875 | 0.9348 |
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| 0.0174 | 8.0 | 12504 | 0.4710 | 0.938 |
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| 0.0135 | 9.0 | 14067 | 0.5213 | 0.9333 |
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| 0.0122 | 10.0 | 15630 | 0.5069 | 0.9366 |
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| 0.0132 | 11.0 | 17193 | 0.5394 | 0.9326 |
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| 0.0067 | 12.0 | 18756 | 0.5691 | 0.9377 |
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| 0.0023 | 13.0 | 20319 | 0.5857 | 0.9368 |
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| 0.0043 | 14.0 | 21882 | 0.5734 | 0.9395 |
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| 0.0048 | 15.0 | 23445 | 0.5936 | 0.9388 |
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| 0.0046 | 16.0 | 25008 | 0.5803 | 0.9389 |
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| 0.0032 | 17.0 | 26571 | 0.5693 | 0.9402 |
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| 0.0006 | 18.0 | 28134 | 0.6308 | 0.9396 |
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| 0.0016 | 19.0 | 29697 | 0.6221 | 0.9402 |
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| 0.0008 | 20.0 | 31260 | 0.6296 | 0.9405 |
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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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