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--- |
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base_model: aubmindlab/bert-base-arabertv02 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: arabert_cross_relevance_task1_fold0 |
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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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# arabert_cross_relevance_task1_fold0 |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1907 |
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- Qwk: 0.0246 |
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- Mse: 0.1907 |
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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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |
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|:-------------:|:------:|:----:|:---------------:|:-------:|:------:| |
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| No log | 0.0351 | 2 | 1.1829 | -0.0050 | 1.1829 | |
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| No log | 0.0702 | 4 | 0.2409 | 0.0099 | 0.2409 | |
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| No log | 0.1053 | 6 | 0.1676 | -0.0484 | 0.1676 | |
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| No log | 0.1404 | 8 | 0.1570 | 0.0130 | 0.1570 | |
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| No log | 0.1754 | 10 | 0.3161 | 0.0173 | 0.3161 | |
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| No log | 0.2105 | 12 | 0.6111 | 0.0144 | 0.6111 | |
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| No log | 0.2456 | 14 | 0.4643 | 0.0505 | 0.4643 | |
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| No log | 0.2807 | 16 | 0.3698 | 0.0345 | 0.3698 | |
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| No log | 0.3158 | 18 | 0.2920 | 0.0181 | 0.2920 | |
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| No log | 0.3509 | 20 | 0.2091 | 0.0235 | 0.2091 | |
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| No log | 0.3860 | 22 | 0.1792 | 0.0092 | 0.1792 | |
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| No log | 0.4211 | 24 | 0.1670 | 0.0386 | 0.1670 | |
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| No log | 0.4561 | 26 | 0.1654 | 0.0258 | 0.1654 | |
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| No log | 0.4912 | 28 | 0.1730 | 0.0081 | 0.1730 | |
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| No log | 0.5263 | 30 | 0.1851 | 0.0141 | 0.1851 | |
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| No log | 0.5614 | 32 | 0.2064 | 0.0092 | 0.2064 | |
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| No log | 0.5965 | 34 | 0.2253 | 0.0270 | 0.2253 | |
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| No log | 0.6316 | 36 | 0.2300 | 0.0355 | 0.2300 | |
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| No log | 0.6667 | 38 | 0.2391 | 0.0339 | 0.2391 | |
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| No log | 0.7018 | 40 | 0.2358 | 0.0339 | 0.2358 | |
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| No log | 0.7368 | 42 | 0.2370 | 0.0300 | 0.2370 | |
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| No log | 0.7719 | 44 | 0.2370 | 0.0361 | 0.2370 | |
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| No log | 0.8070 | 46 | 0.2312 | 0.0323 | 0.2312 | |
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| No log | 0.8421 | 48 | 0.2215 | 0.0323 | 0.2215 | |
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| No log | 0.8772 | 50 | 0.2101 | 0.0358 | 0.2101 | |
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| No log | 0.9123 | 52 | 0.2006 | 0.0212 | 0.2006 | |
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| No log | 0.9474 | 54 | 0.1943 | 0.0246 | 0.1943 | |
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| No log | 0.9825 | 56 | 0.1907 | 0.0246 | 0.1907 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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