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--- |
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library_name: transformers |
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license: mit |
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base_model: deepset/gbert-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: gbert-large-topic_classification |
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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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# gbert-large-topic_classification |
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This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5093 |
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- Precision: 0.9100 |
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- Recall: 0.8993 |
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- F1: 0.9042 |
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- Accuracy: 0.9167 |
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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: 16 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 44 | 0.6465 | 0.8897 | 0.8138 | 0.8179 | 0.8480 | |
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| No log | 2.0 | 88 | 0.2949 | 0.9116 | 0.9110 | 0.9106 | 0.9118 | |
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| No log | 3.0 | 132 | 0.4110 | 0.9298 | 0.8939 | 0.9020 | 0.9167 | |
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| No log | 4.0 | 176 | 0.6242 | 0.9261 | 0.8756 | 0.8911 | 0.9020 | |
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| No log | 5.0 | 220 | 0.5606 | 0.9208 | 0.8757 | 0.8897 | 0.9020 | |
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| No log | 6.0 | 264 | 0.6164 | 0.9201 | 0.8867 | 0.9001 | 0.9069 | |
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| No log | 7.0 | 308 | 0.4898 | 0.9155 | 0.9001 | 0.9071 | 0.9167 | |
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| No log | 8.0 | 352 | 0.4999 | 0.9191 | 0.9029 | 0.9102 | 0.9216 | |
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| No log | 9.0 | 396 | 0.5073 | 0.9100 | 0.8993 | 0.9042 | 0.9167 | |
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| No log | 10.0 | 440 | 0.5093 | 0.9100 | 0.8993 | 0.9042 | 0.9167 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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