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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_vocabulary_task4_fold3 |
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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_vocabulary_task4_fold3 |
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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: 0.9487 |
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- Qwk: 0.7917 |
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- Mse: 0.9487 |
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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 | 0.0308 | 2 | 2.5656 | 0.1026 | 2.5656 | |
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| No log | 0.0615 | 4 | 1.5800 | 0.2273 | 1.5800 | |
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| No log | 0.0923 | 6 | 1.4668 | 0.3238 | 1.4668 | |
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| No log | 0.1231 | 8 | 1.7439 | 0.5345 | 1.7439 | |
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| No log | 0.1538 | 10 | 1.8731 | 0.5182 | 1.8731 | |
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| No log | 0.1846 | 12 | 1.6136 | 0.5153 | 1.6136 | |
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| No log | 0.2154 | 14 | 1.0770 | 0.6447 | 1.0770 | |
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| No log | 0.2462 | 16 | 0.8334 | 0.6452 | 0.8334 | |
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| No log | 0.2769 | 18 | 0.8987 | 0.6213 | 0.8987 | |
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| No log | 0.3077 | 20 | 1.0528 | 0.6192 | 1.0528 | |
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| No log | 0.3385 | 22 | 1.1536 | 0.6127 | 1.1536 | |
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| No log | 0.3692 | 24 | 1.1237 | 0.6677 | 1.1237 | |
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| No log | 0.4 | 26 | 1.0225 | 0.7612 | 1.0225 | |
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| No log | 0.4308 | 28 | 0.9282 | 0.7931 | 0.9282 | |
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| No log | 0.4615 | 30 | 0.8550 | 0.7997 | 0.8550 | |
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| No log | 0.4923 | 32 | 0.8655 | 0.8051 | 0.8655 | |
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| No log | 0.5231 | 34 | 0.8784 | 0.7955 | 0.8784 | |
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| No log | 0.5538 | 36 | 0.9842 | 0.7843 | 0.9842 | |
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| No log | 0.5846 | 38 | 0.9740 | 0.7860 | 0.9740 | |
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| No log | 0.6154 | 40 | 0.9578 | 0.7855 | 0.9578 | |
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| No log | 0.6462 | 42 | 0.8675 | 0.7868 | 0.8675 | |
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| No log | 0.6769 | 44 | 0.8691 | 0.7893 | 0.8691 | |
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| No log | 0.7077 | 46 | 0.9121 | 0.7886 | 0.9121 | |
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| No log | 0.7385 | 48 | 0.9594 | 0.7961 | 0.9594 | |
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| No log | 0.7692 | 50 | 0.9137 | 0.7879 | 0.9137 | |
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| No log | 0.8 | 52 | 0.8811 | 0.7869 | 0.8811 | |
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| No log | 0.8308 | 54 | 0.8791 | 0.7869 | 0.8791 | |
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| No log | 0.8615 | 56 | 0.9161 | 0.7964 | 0.9161 | |
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| No log | 0.8923 | 58 | 0.9349 | 0.7936 | 0.9349 | |
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| No log | 0.9231 | 60 | 0.9520 | 0.7971 | 0.9520 | |
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| No log | 0.9538 | 62 | 0.9575 | 0.7917 | 0.9575 | |
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| No log | 0.9846 | 64 | 0.9487 | 0.7917 | 0.9487 | |
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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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