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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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base_model: distilbert-base-uncased |
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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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type: text-classification |
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name: 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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- type: accuracy |
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value: 0.9071100917431193 |
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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-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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