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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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- f1 |
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base_model: distilbert-base-uncased |
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model-index: |
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- name: distilbert-base-uncased-finetuned-dwnews-categories |
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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-base-uncased-finetuned-dwnews-categories |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8331 |
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- F1: 0.7310 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 2.0432 | 0.3 | 30 | 1.8112 | 0.2093 | |
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| 1.7228 | 0.6 | 60 | 1.4949 | 0.3650 | |
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| 1.3799 | 0.9 | 90 | 1.2691 | 0.5838 | |
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| 1.2261 | 1.2 | 120 | 1.1287 | 0.6345 | |
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| 1.0695 | 1.5 | 150 | 1.0383 | 0.6723 | |
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| 0.9634 | 1.8 | 180 | 0.9570 | 0.7279 | |
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| 0.9289 | 2.1 | 210 | 0.9106 | 0.7435 | |
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| 0.8258 | 2.4 | 240 | 0.9380 | 0.7130 | |
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| 0.7692 | 2.7 | 270 | 0.8708 | 0.7262 | |
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| 0.7542 | 3.0 | 300 | 0.8568 | 0.7350 | |
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| 0.6584 | 3.3 | 330 | 0.8447 | 0.7368 | |
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| 0.5871 | 3.6 | 360 | 0.8517 | 0.7226 | |
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| 0.6528 | 3.9 | 390 | 0.8471 | 0.7290 | |
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| 0.5805 | 4.2 | 420 | 0.8085 | 0.7291 | |
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| 0.5904 | 4.5 | 450 | 0.8331 | 0.7310 | |
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| 0.4877 | 4.8 | 480 | 0.8334 | 0.7209 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.0 |
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- Tokenizers 0.13.2 |
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