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update model card README.md
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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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- glue
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metrics:
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- accuracy
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model-index:
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- name: distilbert-base-uncased-finetuned-sst2
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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: glue
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type: glue
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config: sst2
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split: train
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args: sst2
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9071100917431193
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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-finetuned-sst2
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2842
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- Accuracy: 0.9071
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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: 5
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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 | 0.02 | 100 | 0.3316 | 0.8624 |
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| No log | 0.05 | 200 | 0.3357 | 0.8612 |
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| No log | 0.07 | 300 | 0.3996 | 0.8383 |
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| No log | 0.1 | 400 | 0.3012 | 0.8716 |
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| 0.3421 | 0.12 | 500 | 0.3227 | 0.8693 |
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| 0.3421 | 0.14 | 600 | 0.3643 | 0.8727 |
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| 0.3421 | 0.17 | 700 | 0.2734 | 0.8853 |
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| 0.3421 | 0.19 | 800 | 0.3077 | 0.8945 |
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| 0.3421 | 0.21 | 900 | 0.2709 | 0.9002 |
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| 0.2705 | 0.24 | 1000 | 0.2737 | 0.8899 |
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| 0.2705 | 0.26 | 1100 | 0.3079 | 0.8979 |
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| 0.2705 | 0.29 | 1200 | 0.2713 | 0.8968 |
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| 0.2705 | 0.31 | 1300 | 0.2505 | 0.8933 |
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| 0.2705 | 0.33 | 1400 | 0.2932 | 0.8922 |
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| 0.239 | 0.36 | 1500 | 0.2842 | 0.9071 |
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| 0.239 | 0.38 | 1600 | 0.2509 | 0.9014 |
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| 0.239 | 0.4 | 1700 | 0.2819 | 0.8853 |
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| 0.239 | 0.43 | 1800 | 0.2515 | 0.8956 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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