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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased-finetuned-sst-2-english |
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tags: |
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- generated_from_trainer |
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datasets: |
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- sst2 |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilbert_base_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: sst2 |
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type: sst2 |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9151376146788991 |
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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_SST2 |
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This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the sst2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3690 |
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- Accuracy: 0.9151 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 1 |
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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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| 0.1335 | 0.06 | 500 | 0.5579 | 0.8911 | |
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| 0.1666 | 0.12 | 1000 | 0.5413 | 0.8876 | |
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| 0.1778 | 0.18 | 1500 | 0.7077 | 0.8544 | |
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| 0.1746 | 0.24 | 2000 | 0.5727 | 0.875 | |
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| 0.1632 | 0.3 | 2500 | 0.4972 | 0.8979 | |
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| 0.1675 | 0.36 | 3000 | 0.4742 | 0.8991 | |
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| 0.1573 | 0.42 | 3500 | 0.4943 | 0.8956 | |
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| 0.1525 | 0.48 | 4000 | 0.4907 | 0.8819 | |
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| 0.1394 | 0.53 | 4500 | 0.5010 | 0.8899 | |
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| 0.1458 | 0.59 | 5000 | 0.5461 | 0.8876 | |
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| 0.1588 | 0.65 | 5500 | 0.3364 | 0.9094 | |
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| 0.1373 | 0.71 | 6000 | 0.4198 | 0.9163 | |
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| 0.138 | 0.77 | 6500 | 0.3466 | 0.9128 | |
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| 0.1383 | 0.83 | 7000 | 0.4064 | 0.9094 | |
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| 0.1371 | 0.89 | 7500 | 0.4083 | 0.9002 | |
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| 0.1373 | 0.95 | 8000 | 0.3690 | 0.9151 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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