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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_fold6 |
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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_fold6 |
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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: 0.3809 |
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- Qwk: 0.7212 |
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- Mse: 0.3803 |
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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 | 0.0290 | 2 | 3.5915 | 0.0135 | 3.5774 | |
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| No log | 0.0580 | 4 | 1.6728 | 0.1066 | 1.6543 | |
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| No log | 0.0870 | 6 | 0.9207 | 0.3071 | 0.9146 | |
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| No log | 0.1159 | 8 | 0.9451 | 0.4183 | 0.9392 | |
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| No log | 0.1449 | 10 | 1.0092 | 0.4761 | 1.0019 | |
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| No log | 0.1739 | 12 | 0.8467 | 0.4077 | 0.8353 | |
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| No log | 0.2029 | 14 | 0.7589 | 0.4123 | 0.7471 | |
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| No log | 0.2319 | 16 | 0.6332 | 0.4728 | 0.6243 | |
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| No log | 0.2609 | 18 | 0.6097 | 0.5641 | 0.6051 | |
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| No log | 0.2899 | 20 | 0.5389 | 0.5141 | 0.5354 | |
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| No log | 0.3188 | 22 | 0.5073 | 0.5047 | 0.5034 | |
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| No log | 0.3478 | 24 | 0.4996 | 0.5613 | 0.4954 | |
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| No log | 0.3768 | 26 | 0.4724 | 0.5931 | 0.4689 | |
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| No log | 0.4058 | 28 | 0.4067 | 0.6836 | 0.4044 | |
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| No log | 0.4348 | 30 | 0.4385 | 0.8033 | 0.4374 | |
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| No log | 0.4638 | 32 | 0.4624 | 0.8118 | 0.4616 | |
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| No log | 0.4928 | 34 | 0.4385 | 0.7922 | 0.4378 | |
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| No log | 0.5217 | 36 | 0.4184 | 0.6922 | 0.4169 | |
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| No log | 0.5507 | 38 | 0.4874 | 0.6033 | 0.4851 | |
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| No log | 0.5797 | 40 | 0.6206 | 0.5584 | 0.6172 | |
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| No log | 0.6087 | 42 | 0.7056 | 0.5187 | 0.7018 | |
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| No log | 0.6377 | 44 | 0.6335 | 0.5490 | 0.6305 | |
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| No log | 0.6667 | 46 | 0.4625 | 0.6195 | 0.4610 | |
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| No log | 0.6957 | 48 | 0.3971 | 0.7571 | 0.3968 | |
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| No log | 0.7246 | 50 | 0.4158 | 0.7849 | 0.4158 | |
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| No log | 0.7536 | 52 | 0.4127 | 0.7821 | 0.4127 | |
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| No log | 0.7826 | 54 | 0.4163 | 0.7855 | 0.4162 | |
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| No log | 0.8116 | 56 | 0.4055 | 0.7826 | 0.4053 | |
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| No log | 0.8406 | 58 | 0.3891 | 0.7730 | 0.3888 | |
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| No log | 0.8696 | 60 | 0.3833 | 0.7639 | 0.3829 | |
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| No log | 0.8986 | 62 | 0.3800 | 0.7588 | 0.3795 | |
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| No log | 0.9275 | 64 | 0.3788 | 0.7357 | 0.3783 | |
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| No log | 0.9565 | 66 | 0.3800 | 0.7299 | 0.3795 | |
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| No log | 0.9855 | 68 | 0.3809 | 0.7212 | 0.3803 | |
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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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