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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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base_model: distilbert-base-uncased |
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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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type: text-classification |
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name: 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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- type: accuracy |
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value: 0.9214 |
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name: Accuracy |
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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 an imdb dataset where an evaluation of 5000 samples was created by splitting the training set. |
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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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This model was trained for the introduction to Natural language processing course of [EPITA](https://www.epita.fr/). |
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## Training and evaluation data |
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The training/evaluation split was generated using a `seed` of 42 and a `test_size` of 0.2. |
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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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