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README.md
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---
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license: apache-2.0
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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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- f1
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model-index:
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- name: tiny-vanilla-target-rotten_tomatoes
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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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# tiny-vanilla-target-rotten_tomatoes
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This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7243
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- Accuracy: 0.7674
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- F1: 0.7672
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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: constant
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- training_steps: 5000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.628 | 1.87 | 500 | 0.5538 | 0.7195 | 0.7194 |
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| 0.5067 | 3.75 | 1000 | 0.5213 | 0.7411 | 0.7398 |
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| 0.4249 | 5.62 | 1500 | 0.5142 | 0.7570 | 0.7562 |
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| 0.3566 | 7.49 | 2000 | 0.5391 | 0.7608 | 0.7598 |
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| 0.3012 | 9.36 | 2500 | 0.5747 | 0.7720 | 0.7719 |
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| 0.2553 | 11.24 | 3000 | 0.6101 | 0.7655 | 0.7650 |
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| 0.2106 | 13.11 | 3500 | 0.7000 | 0.7636 | 0.7627 |
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| 0.1766 | 14.98 | 4000 | 0.7243 | 0.7674 | 0.7672 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu116
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- Datasets 2.8.1.dev0
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- Tokenizers 0.13.2
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