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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_baseline_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_baseline_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: 0.2514 |
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- Qwk: 0.0808 |
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- Mse: 0.2559 |
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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: 5 |
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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 | 0.3333 | 2 | 1.1076 | -0.0049 | 1.0949 | |
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| No log | 0.6667 | 4 | 0.2779 | 0.0 | 0.2800 | |
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| No log | 1.0 | 6 | 0.2271 | 0.3467 | 0.2294 | |
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| No log | 1.3333 | 8 | 0.2361 | 0.1667 | 0.2359 | |
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| No log | 1.6667 | 10 | 0.1985 | 0.1250 | 0.2028 | |
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| No log | 2.0 | 12 | 0.2232 | 0.0 | 0.2304 | |
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| No log | 2.3333 | 14 | 0.2167 | 0.0 | 0.2237 | |
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| No log | 2.6667 | 16 | 0.2206 | 0.0 | 0.2259 | |
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| No log | 3.0 | 18 | 0.2075 | 0.0 | 0.2127 | |
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| No log | 3.3333 | 20 | 0.2078 | 0.0 | 0.2132 | |
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| No log | 3.6667 | 22 | 0.2183 | 0.0 | 0.2235 | |
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| No log | 4.0 | 24 | 0.2326 | 0.0 | 0.2375 | |
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| No log | 4.3333 | 26 | 0.2498 | 0.0392 | 0.2543 | |
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| No log | 4.6667 | 28 | 0.2547 | 0.0392 | 0.2590 | |
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| No log | 5.0 | 30 | 0.2514 | 0.0808 | 0.2559 | |
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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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