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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: BertAbstractComp |
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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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# BertAbstractComp |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7130 |
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- Accuracy: 0.8062 |
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- Precision: 0.4972 |
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- Recall: 0.4770 |
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- F1: 0.4772 |
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- Top3: 0.9490 |
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- Top3macro: 0.7051 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Top3 | Top3macro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:---------:| |
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| 0.4172 | 1.0 | 1640 | 0.9578 | 0.7640 | 0.4137 | 0.3973 | 0.3969 | 0.9292 | 0.6189 | |
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| 0.4051 | 2.0 | 3280 | 0.7427 | 0.8024 | 0.4759 | 0.4656 | 0.4654 | 0.9430 | 0.6759 | |
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| 0.2359 | 3.0 | 4920 | 0.8947 | 0.8015 | 0.4735 | 0.4777 | 0.4654 | 0.9402 | 0.6772 | |
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| 0.1543 | 4.0 | 6560 | 0.9402 | 0.8097 | 0.4900 | 0.4890 | 0.4839 | 0.9475 | 0.7062 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.2.1 |
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- Tokenizers 0.19.1 |
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