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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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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: distilbert-base-uncased-imdb
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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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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: 0.9214
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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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# distilbert-base-uncased-imdb
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6252
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- Accuracy: 0.9214
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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: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 128
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- seed: 1337
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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: 10
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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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| 0.2875 | 1.0 | 625 | 0.2286 | 0.9102 |
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| 0.1685 | 2.0 | 1250 | 0.2416 | 0.9128 |
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| 0.1171 | 3.0 | 1875 | 0.3223 | 0.917 |
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| 0.0493 | 4.0 | 2500 | 0.3667 | 0.9162 |
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| 0.023 | 5.0 | 3125 | 0.4074 | 0.92 |
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| 0.015 | 6.0 | 3750 | 0.4291 | 0.9236 |
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| 0.0129 | 7.0 | 4375 | 0.5452 | 0.9194 |
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| 0.0051 | 8.0 | 5000 | 0.5886 | 0.9146 |
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| 0.0027 | 9.0 | 5625 | 0.6310 | 0.9186 |
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| 0.002 | 10.0 | 6250 | 0.6252 | 0.9214 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0+cu113
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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