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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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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: DistilBert-finetuned-Hackaton |
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results: [] |
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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-finetuned-Hackaton |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1456 |
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- Accuracy: 0.4283 |
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- F1: 0.4344 |
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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: 1e-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: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 2.3155 | 1.0 | 338 | 2.6640 | 0.33 | 0.3161 | |
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| 2.2064 | 2.0 | 676 | 2.5991 | 0.3283 | 0.3094 | |
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| 2.0703 | 3.0 | 1014 | 2.5172 | 0.3467 | 0.3347 | |
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| 2.0222 | 4.0 | 1352 | 2.4497 | 0.3567 | 0.3434 | |
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| 1.9197 | 5.0 | 1690 | 2.3951 | 0.375 | 0.3639 | |
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| 1.8334 | 6.0 | 2028 | 2.3398 | 0.375 | 0.3646 | |
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| 1.7327 | 7.0 | 2366 | 2.3231 | 0.3833 | 0.3749 | |
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| 1.6621 | 8.0 | 2704 | 2.3040 | 0.3867 | 0.3787 | |
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| 1.5902 | 9.0 | 3042 | 2.2702 | 0.3883 | 0.3809 | |
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| 1.5554 | 10.0 | 3380 | 2.2230 | 0.4167 | 0.4143 | |
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| 1.5008 | 11.0 | 3718 | 2.2277 | 0.4067 | 0.3999 | |
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| 1.4451 | 12.0 | 4056 | 2.2023 | 0.4033 | 0.4025 | |
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| 1.3788 | 13.0 | 4394 | 2.1953 | 0.41 | 0.4066 | |
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| 1.3418 | 14.0 | 4732 | 2.1774 | 0.4083 | 0.4036 | |
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| 1.2689 | 15.0 | 5070 | 2.1798 | 0.41 | 0.4123 | |
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| 1.2495 | 16.0 | 5408 | 2.1700 | 0.4233 | 0.4228 | |
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| 1.1946 | 17.0 | 5746 | 2.1653 | 0.42 | 0.4241 | |
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| 1.1652 | 18.0 | 6084 | 2.1672 | 0.4283 | 0.4279 | |
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| 1.1428 | 19.0 | 6422 | 2.1631 | 0.4217 | 0.4259 | |
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| 1.1027 | 20.0 | 6760 | 2.1501 | 0.4133 | 0.4189 | |
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| 1.063 | 21.0 | 7098 | 2.1522 | 0.4183 | 0.4244 | |
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| 1.0621 | 22.0 | 7436 | 2.1480 | 0.42 | 0.4258 | |
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| 1.0412 | 23.0 | 7774 | 2.1491 | 0.4217 | 0.4285 | |
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| 1.0311 | 24.0 | 8112 | 2.1493 | 0.4267 | 0.4333 | |
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| 1.0195 | 25.0 | 8450 | 2.1456 | 0.4283 | 0.4344 | |
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### Framework versions |
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- Transformers 4.24.0 |
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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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