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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_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_relevance_task1_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: 0.3732 |
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- Qwk: 0.2161 |
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- Mse: 0.3733 |
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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: 64 |
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- eval_batch_size: 64 |
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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: 10 |
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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 | 0.1333 | 2 | 0.9235 | 0.0305 | 0.9241 | |
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| No log | 0.2667 | 4 | 0.4213 | 0.0752 | 0.4205 | |
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| No log | 0.4 | 6 | 0.4900 | 0.2872 | 0.4904 | |
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| No log | 0.5333 | 8 | 0.3989 | 0.1492 | 0.3997 | |
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| No log | 0.6667 | 10 | 0.2875 | 0.0828 | 0.2881 | |
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| No log | 0.8 | 12 | 0.3103 | 0.1946 | 0.3107 | |
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| No log | 0.9333 | 14 | 0.3505 | 0.1869 | 0.3507 | |
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| No log | 1.0667 | 16 | 0.2987 | 0.2328 | 0.2991 | |
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| No log | 1.2 | 18 | 0.2743 | 0.1987 | 0.2749 | |
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| No log | 1.3333 | 20 | 0.2678 | 0.1801 | 0.2685 | |
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| No log | 1.4667 | 22 | 0.2718 | 0.2380 | 0.2723 | |
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| No log | 1.6 | 24 | 0.2750 | 0.2484 | 0.2754 | |
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| No log | 1.7333 | 26 | 0.2802 | 0.2407 | 0.2807 | |
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| No log | 1.8667 | 28 | 0.2967 | 0.2647 | 0.2971 | |
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| No log | 2.0 | 30 | 0.3002 | 0.2386 | 0.3005 | |
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| No log | 2.1333 | 32 | 0.3042 | 0.2307 | 0.3046 | |
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| No log | 2.2667 | 34 | 0.2836 | 0.2266 | 0.2840 | |
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| No log | 2.4 | 36 | 0.2566 | 0.2275 | 0.2571 | |
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| No log | 2.5333 | 38 | 0.2566 | 0.2726 | 0.2572 | |
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| No log | 2.6667 | 40 | 0.2685 | 0.2318 | 0.2689 | |
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| No log | 2.8 | 42 | 0.3239 | 0.2291 | 0.3238 | |
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| No log | 2.9333 | 44 | 0.3137 | 0.2140 | 0.3139 | |
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| No log | 3.0667 | 46 | 0.2868 | 0.2462 | 0.2874 | |
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| No log | 3.2 | 48 | 0.2840 | 0.2475 | 0.2845 | |
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| No log | 3.3333 | 50 | 0.2972 | 0.2539 | 0.2975 | |
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| No log | 3.4667 | 52 | 0.2987 | 0.2373 | 0.2989 | |
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| No log | 3.6 | 54 | 0.2922 | 0.2472 | 0.2925 | |
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| No log | 3.7333 | 56 | 0.2979 | 0.2276 | 0.2983 | |
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| No log | 3.8667 | 58 | 0.3082 | 0.2134 | 0.3086 | |
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| No log | 4.0 | 60 | 0.3245 | 0.2197 | 0.3249 | |
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| No log | 4.1333 | 62 | 0.3302 | 0.2197 | 0.3305 | |
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| No log | 4.2667 | 64 | 0.3164 | 0.2079 | 0.3169 | |
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| No log | 4.4 | 66 | 0.3410 | 0.2131 | 0.3413 | |
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| No log | 4.5333 | 68 | 0.3844 | 0.2178 | 0.3845 | |
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| No log | 4.6667 | 70 | 0.3887 | 0.2178 | 0.3888 | |
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| No log | 4.8 | 72 | 0.3995 | 0.2096 | 0.3996 | |
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| No log | 4.9333 | 74 | 0.3677 | 0.2141 | 0.3679 | |
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| No log | 5.0667 | 76 | 0.3517 | 0.2188 | 0.3520 | |
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| No log | 5.2 | 78 | 0.3437 | 0.2188 | 0.3439 | |
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| No log | 5.3333 | 80 | 0.3781 | 0.2096 | 0.3782 | |
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| No log | 5.4667 | 82 | 0.4079 | 0.1975 | 0.4080 | |
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| No log | 5.6 | 84 | 0.4051 | 0.2133 | 0.4052 | |
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| No log | 5.7333 | 86 | 0.3469 | 0.2313 | 0.3471 | |
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| No log | 5.8667 | 88 | 0.3091 | 0.2317 | 0.3095 | |
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| No log | 6.0 | 90 | 0.3034 | 0.2341 | 0.3039 | |
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| No log | 6.1333 | 92 | 0.3187 | 0.2175 | 0.3191 | |
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| No log | 6.2667 | 94 | 0.3556 | 0.2123 | 0.3558 | |
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| No log | 6.4 | 96 | 0.4256 | 0.1936 | 0.4256 | |
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| No log | 6.5333 | 98 | 0.4370 | 0.1899 | 0.4370 | |
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| No log | 6.6667 | 100 | 0.4141 | 0.2053 | 0.4142 | |
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| No log | 6.8 | 102 | 0.4062 | 0.2053 | 0.4063 | |
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| No log | 6.9333 | 104 | 0.3722 | 0.2178 | 0.3723 | |
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| No log | 7.0667 | 106 | 0.3420 | 0.2313 | 0.3423 | |
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| No log | 7.2 | 108 | 0.3323 | 0.2337 | 0.3326 | |
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| No log | 7.3333 | 110 | 0.3482 | 0.2161 | 0.3484 | |
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| No log | 7.4667 | 112 | 0.3690 | 0.2178 | 0.3691 | |
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| No log | 7.6 | 114 | 0.3867 | 0.2169 | 0.3868 | |
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| No log | 7.7333 | 116 | 0.4039 | 0.2029 | 0.4039 | |
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| No log | 7.8667 | 118 | 0.4092 | 0.2029 | 0.4091 | |
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| No log | 8.0 | 120 | 0.4179 | 0.2012 | 0.4178 | |
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| No log | 8.1333 | 122 | 0.4160 | 0.2089 | 0.4160 | |
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| No log | 8.2667 | 124 | 0.4199 | 0.2012 | 0.4199 | |
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| No log | 8.4 | 126 | 0.4338 | 0.1899 | 0.4337 | |
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| No log | 8.5333 | 128 | 0.4437 | 0.1935 | 0.4436 | |
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| No log | 8.6667 | 130 | 0.4404 | 0.1973 | 0.4403 | |
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| No log | 8.8 | 132 | 0.4283 | 0.2012 | 0.4282 | |
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| No log | 8.9333 | 134 | 0.4152 | 0.2012 | 0.4151 | |
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| No log | 9.0667 | 136 | 0.3937 | 0.2089 | 0.3937 | |
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| No log | 9.2 | 138 | 0.3753 | 0.2141 | 0.3753 | |
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| No log | 9.3333 | 140 | 0.3664 | 0.2097 | 0.3665 | |
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| No log | 9.4667 | 142 | 0.3644 | 0.2097 | 0.3645 | |
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| No log | 9.6 | 144 | 0.3651 | 0.2097 | 0.3652 | |
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| No log | 9.7333 | 146 | 0.3680 | 0.2097 | 0.3681 | |
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| No log | 9.8667 | 148 | 0.3713 | 0.2097 | 0.3714 | |
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| No log | 10.0 | 150 | 0.3732 | 0.2161 | 0.3733 | |
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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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