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--- |
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base_model: facebook/bart-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- datasets/all_binary_and_xe_ey_fae_counterfactual |
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metrics: |
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- accuracy |
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model-index: |
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- name: bart-base-finetuned-xe_ey_fae |
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results: |
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- task: |
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name: Masked Language Modeling |
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type: fill-mask |
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dataset: |
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name: datasets/all_binary_and_xe_ey_fae_counterfactual |
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type: datasets/all_binary_and_xe_ey_fae_counterfactual |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7180178883360112 |
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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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# bart-base-finetuned-xe_ey_fae |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the datasets/all_binary_and_xe_ey_fae_counterfactual dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3945 |
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- Accuracy: 0.7180 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 100 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 3.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 5.4226 | 0.06 | 500 | 3.8138 | 0.3628 | |
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| 4.0408 | 0.12 | 1000 | 3.0576 | 0.4630 | |
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| 3.4979 | 0.18 | 1500 | 2.7016 | 0.5133 | |
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| 3.1691 | 0.24 | 2000 | 2.4880 | 0.5431 | |
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| 2.9564 | 0.3 | 2500 | 2.3309 | 0.5644 | |
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| 2.8078 | 0.35 | 3000 | 2.2320 | 0.5792 | |
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| 2.6741 | 0.41 | 3500 | 2.1506 | 0.5924 | |
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| 2.5323 | 0.47 | 4000 | 1.9846 | 0.6176 | |
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| 2.3678 | 0.53 | 4500 | 1.8813 | 0.6375 | |
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| 2.25 | 0.59 | 5000 | 1.8100 | 0.6497 | |
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| 2.1795 | 0.65 | 5500 | 1.7632 | 0.6579 | |
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| 2.1203 | 0.71 | 6000 | 1.7238 | 0.6646 | |
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| 2.0764 | 0.77 | 6500 | 1.6856 | 0.6713 | |
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| 2.026 | 0.83 | 7000 | 1.6569 | 0.6760 | |
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| 1.9942 | 0.89 | 7500 | 1.6309 | 0.6803 | |
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| 1.9665 | 0.95 | 8000 | 1.6122 | 0.6836 | |
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| 1.9395 | 1.0 | 8500 | 1.5913 | 0.6866 | |
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| 1.9155 | 1.06 | 9000 | 1.5758 | 0.6895 | |
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| 1.8828 | 1.12 | 9500 | 1.5607 | 0.6918 | |
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| 1.8721 | 1.18 | 10000 | 1.5422 | 0.6948 | |
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| 1.8474 | 1.24 | 10500 | 1.5320 | 0.6964 | |
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| 1.8293 | 1.3 | 11000 | 1.5214 | 0.6978 | |
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| 1.8129 | 1.36 | 11500 | 1.5102 | 0.6998 | |
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| 1.8148 | 1.42 | 12000 | 1.5010 | 0.7013 | |
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| 1.7903 | 1.48 | 12500 | 1.4844 | 0.7038 | |
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| 1.7815 | 1.54 | 13000 | 1.4823 | 0.7039 | |
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| 1.7637 | 1.6 | 13500 | 1.4746 | 0.7052 | |
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| 1.7623 | 1.66 | 14000 | 1.4701 | 0.7061 | |
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| 1.7402 | 1.71 | 14500 | 1.4598 | 0.7076 | |
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| 1.7376 | 1.77 | 15000 | 1.4519 | 0.7090 | |
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| 1.7287 | 1.83 | 15500 | 1.4501 | 0.7101 | |
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| 1.7273 | 1.89 | 16000 | 1.4409 | 0.7107 | |
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| 1.7119 | 1.95 | 16500 | 1.4314 | 0.7125 | |
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| 1.7098 | 2.01 | 17000 | 1.4269 | 0.7129 | |
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| 1.6978 | 2.07 | 17500 | 1.4275 | 0.7132 | |
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| 1.698 | 2.13 | 18000 | 1.4218 | 0.7140 | |
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| 1.6837 | 2.19 | 18500 | 1.4151 | 0.7147 | |
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| 1.6908 | 2.25 | 19000 | 1.4137 | 0.7149 | |
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| 1.6902 | 2.31 | 19500 | 1.4085 | 0.7161 | |
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| 1.6741 | 2.36 | 20000 | 1.4121 | 0.7154 | |
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| 1.6823 | 2.42 | 20500 | 1.4037 | 0.7165 | |
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| 1.6692 | 2.48 | 21000 | 1.4039 | 0.7164 | |
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| 1.6669 | 2.54 | 21500 | 1.4015 | 0.7172 | |
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| 1.6613 | 2.6 | 22000 | 1.3979 | 0.7179 | |
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| 1.664 | 2.66 | 22500 | 1.3960 | 0.7180 | |
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| 1.6615 | 2.72 | 23000 | 1.4012 | 0.7172 | |
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| 1.6627 | 2.78 | 23500 | 1.3974 | 0.7178 | |
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| 1.6489 | 2.84 | 24000 | 1.3948 | 0.7182 | |
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| 1.6429 | 2.9 | 24500 | 1.3921 | 0.7184 | |
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| 1.6477 | 2.96 | 25000 | 1.3910 | 0.7182 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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