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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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model-index: |
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- name: bert-base-uncased-finetuned-sdg |
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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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# bert-base-uncased-finetuned-sdg |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the OSDG dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3094 |
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- Acc: 0.9195 |
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## Model description |
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Classifies text to the first 16 SDGs! |
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## Intended uses & limitations |
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Assess policy documents, classify text to SDGs, etc. |
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## Training and evaluation data |
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OSDG data. Updated version from October. |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Acc | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.3768 | 1.0 | 269 | 0.3758 | 0.8933 | |
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| 0.2261 | 2.0 | 538 | 0.3088 | 0.9095 | |
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| 0.1038 | 3.0 | 807 | 0.3094 | 0.9195 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.0a0+8a1a93a |
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- Datasets 2.5.2 |
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- Tokenizers 0.13.1 |
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