Instructions to use MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask6_grammar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask6_grammar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask6_grammar")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask6_grammar") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask6_grammar") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files- README.md +318 -0
- config.json +32 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
README.md
ADDED
|
@@ -0,0 +1,318 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
base_model: aubmindlab/bert-base-arabertv02
|
| 4 |
+
tags:
|
| 5 |
+
- generated_from_trainer
|
| 6 |
+
model-index:
|
| 7 |
+
- name: Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask6_mechanics
|
| 8 |
+
results: []
|
| 9 |
+
---
|
| 10 |
+
|
| 11 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 12 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 13 |
+
|
| 14 |
+
# Arabic_CrossPrompt_FineTuningAraBERT_noAug_TestTask6_mechanics
|
| 15 |
+
|
| 16 |
+
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
|
| 17 |
+
It achieves the following results on the evaluation set:
|
| 18 |
+
- Loss: 0.6094
|
| 19 |
+
- Qwk: 0.5646
|
| 20 |
+
- Mse: 0.6094
|
| 21 |
+
- Rmse: 0.7806
|
| 22 |
+
|
| 23 |
+
## Model description
|
| 24 |
+
|
| 25 |
+
More information needed
|
| 26 |
+
|
| 27 |
+
## Intended uses & limitations
|
| 28 |
+
|
| 29 |
+
More information needed
|
| 30 |
+
|
| 31 |
+
## Training and evaluation data
|
| 32 |
+
|
| 33 |
+
More information needed
|
| 34 |
+
|
| 35 |
+
## Training procedure
|
| 36 |
+
|
| 37 |
+
### Training hyperparameters
|
| 38 |
+
|
| 39 |
+
The following hyperparameters were used during training:
|
| 40 |
+
- learning_rate: 2e-05
|
| 41 |
+
- train_batch_size: 8
|
| 42 |
+
- eval_batch_size: 8
|
| 43 |
+
- seed: 42
|
| 44 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 45 |
+
- lr_scheduler_type: linear
|
| 46 |
+
- num_epochs: 100
|
| 47 |
+
|
| 48 |
+
### Training results
|
| 49 |
+
|
| 50 |
+
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|
| 51 |
+
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:------:|
|
| 52 |
+
| No log | 0.0194 | 2 | 4.2525 | -0.0139 | 4.2525 | 2.0621 |
|
| 53 |
+
| No log | 0.0388 | 4 | 2.3872 | 0.0327 | 2.3872 | 1.5451 |
|
| 54 |
+
| No log | 0.0583 | 6 | 1.2721 | 0.0033 | 1.2721 | 1.1279 |
|
| 55 |
+
| No log | 0.0777 | 8 | 0.8541 | 0.0835 | 0.8541 | 0.9242 |
|
| 56 |
+
| No log | 0.0971 | 10 | 0.7555 | 0.2089 | 0.7555 | 0.8692 |
|
| 57 |
+
| No log | 0.1165 | 12 | 0.7707 | 0.2106 | 0.7707 | 0.8779 |
|
| 58 |
+
| No log | 0.1359 | 14 | 0.9472 | 0.0818 | 0.9472 | 0.9732 |
|
| 59 |
+
| No log | 0.1553 | 16 | 0.8553 | 0.1654 | 0.8553 | 0.9248 |
|
| 60 |
+
| No log | 0.1748 | 18 | 0.6460 | 0.3304 | 0.6460 | 0.8038 |
|
| 61 |
+
| No log | 0.1942 | 20 | 1.0433 | 0.1755 | 1.0433 | 1.0214 |
|
| 62 |
+
| No log | 0.2136 | 22 | 1.1332 | 0.1176 | 1.1332 | 1.0645 |
|
| 63 |
+
| No log | 0.2330 | 24 | 0.8071 | 0.2599 | 0.8071 | 0.8984 |
|
| 64 |
+
| No log | 0.2524 | 26 | 0.6354 | 0.3605 | 0.6354 | 0.7971 |
|
| 65 |
+
| No log | 0.2718 | 28 | 0.6136 | 0.2978 | 0.6136 | 0.7833 |
|
| 66 |
+
| No log | 0.2913 | 30 | 0.5818 | 0.3311 | 0.5818 | 0.7628 |
|
| 67 |
+
| No log | 0.3107 | 32 | 0.5778 | 0.3574 | 0.5778 | 0.7601 |
|
| 68 |
+
| No log | 0.3301 | 34 | 0.6523 | 0.3694 | 0.6523 | 0.8077 |
|
| 69 |
+
| No log | 0.3495 | 36 | 0.7375 | 0.3488 | 0.7375 | 0.8588 |
|
| 70 |
+
| No log | 0.3689 | 38 | 0.7014 | 0.3631 | 0.7014 | 0.8375 |
|
| 71 |
+
| No log | 0.3883 | 40 | 0.5815 | 0.4179 | 0.5815 | 0.7626 |
|
| 72 |
+
| No log | 0.4078 | 42 | 0.5401 | 0.4473 | 0.5401 | 0.7349 |
|
| 73 |
+
| No log | 0.4272 | 44 | 0.5602 | 0.4443 | 0.5602 | 0.7485 |
|
| 74 |
+
| No log | 0.4466 | 46 | 0.5628 | 0.3571 | 0.5628 | 0.7502 |
|
| 75 |
+
| No log | 0.4660 | 48 | 0.5219 | 0.4735 | 0.5219 | 0.7224 |
|
| 76 |
+
| No log | 0.4854 | 50 | 0.5453 | 0.5375 | 0.5453 | 0.7384 |
|
| 77 |
+
| No log | 0.5049 | 52 | 0.7426 | 0.4346 | 0.7426 | 0.8618 |
|
| 78 |
+
| No log | 0.5243 | 54 | 0.8191 | 0.4074 | 0.8191 | 0.9050 |
|
| 79 |
+
| No log | 0.5437 | 56 | 0.7050 | 0.4320 | 0.7050 | 0.8396 |
|
| 80 |
+
| No log | 0.5631 | 58 | 0.5587 | 0.5187 | 0.5587 | 0.7475 |
|
| 81 |
+
| No log | 0.5825 | 60 | 0.4918 | 0.4812 | 0.4918 | 0.7013 |
|
| 82 |
+
| No log | 0.6019 | 62 | 0.6113 | 0.2805 | 0.6113 | 0.7818 |
|
| 83 |
+
| No log | 0.6214 | 64 | 0.6609 | 0.2244 | 0.6609 | 0.8129 |
|
| 84 |
+
| No log | 0.6408 | 66 | 0.6605 | 0.2509 | 0.6605 | 0.8127 |
|
| 85 |
+
| No log | 0.6602 | 68 | 0.6463 | 0.2223 | 0.6463 | 0.8039 |
|
| 86 |
+
| No log | 0.6796 | 70 | 0.6559 | 0.2360 | 0.6559 | 0.8099 |
|
| 87 |
+
| No log | 0.6990 | 72 | 0.6623 | 0.2547 | 0.6623 | 0.8138 |
|
| 88 |
+
| No log | 0.7184 | 74 | 0.6145 | 0.3350 | 0.6145 | 0.7839 |
|
| 89 |
+
| No log | 0.7379 | 76 | 0.5681 | 0.4088 | 0.5681 | 0.7537 |
|
| 90 |
+
| No log | 0.7573 | 78 | 0.6130 | 0.3894 | 0.6130 | 0.7829 |
|
| 91 |
+
| No log | 0.7767 | 80 | 0.6727 | 0.3460 | 0.6727 | 0.8202 |
|
| 92 |
+
| No log | 0.7961 | 82 | 0.6223 | 0.3694 | 0.6223 | 0.7889 |
|
| 93 |
+
| No log | 0.8155 | 84 | 0.5937 | 0.4129 | 0.5937 | 0.7705 |
|
| 94 |
+
| No log | 0.8350 | 86 | 0.5397 | 0.4367 | 0.5397 | 0.7346 |
|
| 95 |
+
| No log | 0.8544 | 88 | 0.5527 | 0.4544 | 0.5527 | 0.7435 |
|
| 96 |
+
| No log | 0.8738 | 90 | 0.6461 | 0.4229 | 0.6461 | 0.8038 |
|
| 97 |
+
| No log | 0.8932 | 92 | 0.6917 | 0.4602 | 0.6917 | 0.8317 |
|
| 98 |
+
| No log | 0.9126 | 94 | 0.6081 | 0.4440 | 0.6081 | 0.7798 |
|
| 99 |
+
| No log | 0.9320 | 96 | 0.4825 | 0.5820 | 0.4825 | 0.6946 |
|
| 100 |
+
| No log | 0.9515 | 98 | 0.5107 | 0.5534 | 0.5107 | 0.7146 |
|
| 101 |
+
| No log | 0.9709 | 100 | 0.4973 | 0.5869 | 0.4973 | 0.7052 |
|
| 102 |
+
| No log | 0.9903 | 102 | 0.5108 | 0.5525 | 0.5108 | 0.7147 |
|
| 103 |
+
| No log | 1.0097 | 104 | 0.5262 | 0.5741 | 0.5262 | 0.7254 |
|
| 104 |
+
| No log | 1.0291 | 106 | 0.5966 | 0.5273 | 0.5966 | 0.7724 |
|
| 105 |
+
| No log | 1.0485 | 108 | 0.6250 | 0.5077 | 0.6250 | 0.7905 |
|
| 106 |
+
| No log | 1.0680 | 110 | 0.6002 | 0.5296 | 0.6002 | 0.7747 |
|
| 107 |
+
| No log | 1.0874 | 112 | 0.6358 | 0.4987 | 0.6358 | 0.7974 |
|
| 108 |
+
| No log | 1.1068 | 114 | 0.5974 | 0.5105 | 0.5974 | 0.7729 |
|
| 109 |
+
| No log | 1.1262 | 116 | 0.5770 | 0.5415 | 0.5770 | 0.7596 |
|
| 110 |
+
| No log | 1.1456 | 118 | 0.5854 | 0.5385 | 0.5854 | 0.7651 |
|
| 111 |
+
| No log | 1.1650 | 120 | 0.5931 | 0.5460 | 0.5931 | 0.7701 |
|
| 112 |
+
| No log | 1.1845 | 122 | 0.5379 | 0.5617 | 0.5379 | 0.7334 |
|
| 113 |
+
| No log | 1.2039 | 124 | 0.4832 | 0.5512 | 0.4832 | 0.6951 |
|
| 114 |
+
| No log | 1.2233 | 126 | 0.4809 | 0.5503 | 0.4809 | 0.6935 |
|
| 115 |
+
| No log | 1.2427 | 128 | 0.4820 | 0.5724 | 0.4820 | 0.6943 |
|
| 116 |
+
| No log | 1.2621 | 130 | 0.4581 | 0.5423 | 0.4581 | 0.6768 |
|
| 117 |
+
| No log | 1.2816 | 132 | 0.4706 | 0.6083 | 0.4706 | 0.6860 |
|
| 118 |
+
| No log | 1.3010 | 134 | 0.5381 | 0.5920 | 0.5381 | 0.7335 |
|
| 119 |
+
| No log | 1.3204 | 136 | 0.6493 | 0.5041 | 0.6493 | 0.8058 |
|
| 120 |
+
| No log | 1.3398 | 138 | 0.7216 | 0.4040 | 0.7216 | 0.8495 |
|
| 121 |
+
| No log | 1.3592 | 140 | 0.7310 | 0.2962 | 0.7310 | 0.8550 |
|
| 122 |
+
| No log | 1.3786 | 142 | 0.6616 | 0.3363 | 0.6616 | 0.8134 |
|
| 123 |
+
| No log | 1.3981 | 144 | 0.5552 | 0.5248 | 0.5552 | 0.7451 |
|
| 124 |
+
| No log | 1.4175 | 146 | 0.5021 | 0.5767 | 0.5021 | 0.7086 |
|
| 125 |
+
| No log | 1.4369 | 148 | 0.4966 | 0.5836 | 0.4966 | 0.7047 |
|
| 126 |
+
| No log | 1.4563 | 150 | 0.5866 | 0.5524 | 0.5866 | 0.7659 |
|
| 127 |
+
| No log | 1.4757 | 152 | 0.6704 | 0.5176 | 0.6704 | 0.8188 |
|
| 128 |
+
| No log | 1.4951 | 154 | 0.6141 | 0.5427 | 0.6141 | 0.7836 |
|
| 129 |
+
| No log | 1.5146 | 156 | 0.5205 | 0.5816 | 0.5205 | 0.7215 |
|
| 130 |
+
| No log | 1.5340 | 158 | 0.5364 | 0.5209 | 0.5364 | 0.7324 |
|
| 131 |
+
| No log | 1.5534 | 160 | 0.5937 | 0.5229 | 0.5937 | 0.7705 |
|
| 132 |
+
| No log | 1.5728 | 162 | 0.5823 | 0.5214 | 0.5823 | 0.7631 |
|
| 133 |
+
| No log | 1.5922 | 164 | 0.5534 | 0.5437 | 0.5534 | 0.7439 |
|
| 134 |
+
| No log | 1.6117 | 166 | 0.5393 | 0.5563 | 0.5393 | 0.7344 |
|
| 135 |
+
| No log | 1.6311 | 168 | 0.5079 | 0.5449 | 0.5079 | 0.7126 |
|
| 136 |
+
| No log | 1.6505 | 170 | 0.5207 | 0.5317 | 0.5207 | 0.7216 |
|
| 137 |
+
| No log | 1.6699 | 172 | 0.5226 | 0.5224 | 0.5226 | 0.7229 |
|
| 138 |
+
| No log | 1.6893 | 174 | 0.4880 | 0.4944 | 0.4880 | 0.6985 |
|
| 139 |
+
| No log | 1.7087 | 176 | 0.4910 | 0.4792 | 0.4910 | 0.7007 |
|
| 140 |
+
| No log | 1.7282 | 178 | 0.5097 | 0.4552 | 0.5097 | 0.7139 |
|
| 141 |
+
| No log | 1.7476 | 180 | 0.5065 | 0.4323 | 0.5065 | 0.7117 |
|
| 142 |
+
| No log | 1.7670 | 182 | 0.5153 | 0.4325 | 0.5153 | 0.7178 |
|
| 143 |
+
| No log | 1.7864 | 184 | 0.5317 | 0.4170 | 0.5317 | 0.7292 |
|
| 144 |
+
| No log | 1.8058 | 186 | 0.5433 | 0.4675 | 0.5433 | 0.7371 |
|
| 145 |
+
| No log | 1.8252 | 188 | 0.5522 | 0.4925 | 0.5522 | 0.7431 |
|
| 146 |
+
| No log | 1.8447 | 190 | 0.5242 | 0.5139 | 0.5242 | 0.7240 |
|
| 147 |
+
| No log | 1.8641 | 192 | 0.4887 | 0.5560 | 0.4887 | 0.6991 |
|
| 148 |
+
| No log | 1.8835 | 194 | 0.4886 | 0.5513 | 0.4886 | 0.6990 |
|
| 149 |
+
| No log | 1.9029 | 196 | 0.5096 | 0.5352 | 0.5096 | 0.7138 |
|
| 150 |
+
| No log | 1.9223 | 198 | 0.5313 | 0.5359 | 0.5313 | 0.7289 |
|
| 151 |
+
| No log | 1.9417 | 200 | 0.5302 | 0.5451 | 0.5302 | 0.7281 |
|
| 152 |
+
| No log | 1.9612 | 202 | 0.5257 | 0.5098 | 0.5257 | 0.7251 |
|
| 153 |
+
| No log | 1.9806 | 204 | 0.5491 | 0.5511 | 0.5491 | 0.7410 |
|
| 154 |
+
| No log | 2.0 | 206 | 0.6058 | 0.5288 | 0.6058 | 0.7783 |
|
| 155 |
+
| No log | 2.0194 | 208 | 0.6552 | 0.5109 | 0.6552 | 0.8094 |
|
| 156 |
+
| No log | 2.0388 | 210 | 0.6660 | 0.5101 | 0.6660 | 0.8161 |
|
| 157 |
+
| No log | 2.0583 | 212 | 0.6528 | 0.5382 | 0.6528 | 0.8080 |
|
| 158 |
+
| No log | 2.0777 | 214 | 0.6068 | 0.5445 | 0.6068 | 0.7790 |
|
| 159 |
+
| No log | 2.0971 | 216 | 0.5673 | 0.5704 | 0.5673 | 0.7532 |
|
| 160 |
+
| No log | 2.1165 | 218 | 0.5744 | 0.5656 | 0.5744 | 0.7579 |
|
| 161 |
+
| No log | 2.1359 | 220 | 0.5436 | 0.5793 | 0.5436 | 0.7373 |
|
| 162 |
+
| No log | 2.1553 | 222 | 0.5252 | 0.5362 | 0.5252 | 0.7247 |
|
| 163 |
+
| No log | 2.1748 | 224 | 0.5305 | 0.5222 | 0.5305 | 0.7284 |
|
| 164 |
+
| No log | 2.1942 | 226 | 0.5111 | 0.5457 | 0.5111 | 0.7149 |
|
| 165 |
+
| No log | 2.2136 | 228 | 0.4858 | 0.5573 | 0.4858 | 0.6970 |
|
| 166 |
+
| No log | 2.2330 | 230 | 0.5103 | 0.5660 | 0.5103 | 0.7144 |
|
| 167 |
+
| No log | 2.2524 | 232 | 0.5316 | 0.5610 | 0.5316 | 0.7291 |
|
| 168 |
+
| No log | 2.2718 | 234 | 0.5373 | 0.5578 | 0.5373 | 0.7330 |
|
| 169 |
+
| No log | 2.2913 | 236 | 0.5765 | 0.5456 | 0.5765 | 0.7593 |
|
| 170 |
+
| No log | 2.3107 | 238 | 0.5666 | 0.5624 | 0.5666 | 0.7527 |
|
| 171 |
+
| No log | 2.3301 | 240 | 0.5713 | 0.5528 | 0.5713 | 0.7558 |
|
| 172 |
+
| No log | 2.3495 | 242 | 0.6560 | 0.4942 | 0.6560 | 0.8099 |
|
| 173 |
+
| No log | 2.3689 | 244 | 0.6048 | 0.5063 | 0.6048 | 0.7777 |
|
| 174 |
+
| No log | 2.3883 | 246 | 0.5344 | 0.5061 | 0.5344 | 0.7310 |
|
| 175 |
+
| No log | 2.4078 | 248 | 0.5737 | 0.4125 | 0.5737 | 0.7575 |
|
| 176 |
+
| No log | 2.4272 | 250 | 0.5618 | 0.4583 | 0.5618 | 0.7495 |
|
| 177 |
+
| No log | 2.4466 | 252 | 0.5884 | 0.5009 | 0.5884 | 0.7670 |
|
| 178 |
+
| No log | 2.4660 | 254 | 0.7421 | 0.4739 | 0.7421 | 0.8615 |
|
| 179 |
+
| No log | 2.4854 | 256 | 0.7987 | 0.4423 | 0.7987 | 0.8937 |
|
| 180 |
+
| No log | 2.5049 | 258 | 0.6967 | 0.4894 | 0.6967 | 0.8347 |
|
| 181 |
+
| No log | 2.5243 | 260 | 0.6123 | 0.5569 | 0.6123 | 0.7825 |
|
| 182 |
+
| No log | 2.5437 | 262 | 0.5077 | 0.5541 | 0.5077 | 0.7125 |
|
| 183 |
+
| No log | 2.5631 | 264 | 0.4975 | 0.5591 | 0.4975 | 0.7053 |
|
| 184 |
+
| No log | 2.5825 | 266 | 0.4953 | 0.6139 | 0.4953 | 0.7038 |
|
| 185 |
+
| No log | 2.6019 | 268 | 0.5250 | 0.5962 | 0.5250 | 0.7246 |
|
| 186 |
+
| No log | 2.6214 | 270 | 0.5146 | 0.6277 | 0.5146 | 0.7173 |
|
| 187 |
+
| No log | 2.6408 | 272 | 0.5703 | 0.6047 | 0.5703 | 0.7552 |
|
| 188 |
+
| No log | 2.6602 | 274 | 0.5807 | 0.5921 | 0.5807 | 0.7620 |
|
| 189 |
+
| No log | 2.6796 | 276 | 0.5372 | 0.6161 | 0.5372 | 0.7329 |
|
| 190 |
+
| No log | 2.6990 | 278 | 0.4785 | 0.6238 | 0.4785 | 0.6917 |
|
| 191 |
+
| No log | 2.7184 | 280 | 0.4987 | 0.5888 | 0.4987 | 0.7062 |
|
| 192 |
+
| No log | 2.7379 | 282 | 0.5507 | 0.5375 | 0.5507 | 0.7421 |
|
| 193 |
+
| No log | 2.7573 | 284 | 0.5363 | 0.5474 | 0.5363 | 0.7323 |
|
| 194 |
+
| No log | 2.7767 | 286 | 0.4876 | 0.5508 | 0.4876 | 0.6983 |
|
| 195 |
+
| No log | 2.7961 | 288 | 0.5465 | 0.5784 | 0.5465 | 0.7393 |
|
| 196 |
+
| No log | 2.8155 | 290 | 0.7655 | 0.5037 | 0.7655 | 0.8749 |
|
| 197 |
+
| No log | 2.8350 | 292 | 0.9052 | 0.4506 | 0.9052 | 0.9514 |
|
| 198 |
+
| No log | 2.8544 | 294 | 0.8210 | 0.4720 | 0.8210 | 0.9061 |
|
| 199 |
+
| No log | 2.8738 | 296 | 0.6254 | 0.5025 | 0.6254 | 0.7908 |
|
| 200 |
+
| No log | 2.8932 | 298 | 0.4740 | 0.6017 | 0.4740 | 0.6885 |
|
| 201 |
+
| No log | 2.9126 | 300 | 0.4615 | 0.5310 | 0.4615 | 0.6794 |
|
| 202 |
+
| No log | 2.9320 | 302 | 0.4516 | 0.5381 | 0.4516 | 0.6720 |
|
| 203 |
+
| No log | 2.9515 | 304 | 0.4517 | 0.5461 | 0.4517 | 0.6721 |
|
| 204 |
+
| No log | 2.9709 | 306 | 0.4573 | 0.5547 | 0.4573 | 0.6762 |
|
| 205 |
+
| No log | 2.9903 | 308 | 0.4527 | 0.4903 | 0.4527 | 0.6728 |
|
| 206 |
+
| No log | 3.0097 | 310 | 0.4523 | 0.4913 | 0.4523 | 0.6725 |
|
| 207 |
+
| No log | 3.0291 | 312 | 0.4368 | 0.5250 | 0.4368 | 0.6609 |
|
| 208 |
+
| No log | 3.0485 | 314 | 0.4228 | 0.5751 | 0.4228 | 0.6502 |
|
| 209 |
+
| No log | 3.0680 | 316 | 0.4401 | 0.5659 | 0.4401 | 0.6634 |
|
| 210 |
+
| No log | 3.0874 | 318 | 0.4725 | 0.5194 | 0.4725 | 0.6874 |
|
| 211 |
+
| No log | 3.1068 | 320 | 0.4898 | 0.5674 | 0.4898 | 0.6999 |
|
| 212 |
+
| No log | 3.1262 | 322 | 0.5390 | 0.5565 | 0.5390 | 0.7342 |
|
| 213 |
+
| No log | 3.1456 | 324 | 0.5165 | 0.5731 | 0.5165 | 0.7187 |
|
| 214 |
+
| No log | 3.1650 | 326 | 0.5171 | 0.5919 | 0.5171 | 0.7191 |
|
| 215 |
+
| No log | 3.1845 | 328 | 0.4959 | 0.6539 | 0.4959 | 0.7042 |
|
| 216 |
+
| No log | 3.2039 | 330 | 0.4875 | 0.6517 | 0.4875 | 0.6982 |
|
| 217 |
+
| No log | 3.2233 | 332 | 0.5271 | 0.6586 | 0.5271 | 0.7260 |
|
| 218 |
+
| No log | 3.2427 | 334 | 0.4991 | 0.6524 | 0.4991 | 0.7065 |
|
| 219 |
+
| No log | 3.2621 | 336 | 0.4726 | 0.6451 | 0.4726 | 0.6875 |
|
| 220 |
+
| No log | 3.2816 | 338 | 0.4928 | 0.6422 | 0.4928 | 0.7020 |
|
| 221 |
+
| No log | 3.3010 | 340 | 0.5734 | 0.5797 | 0.5734 | 0.7572 |
|
| 222 |
+
| No log | 3.3204 | 342 | 0.7362 | 0.5185 | 0.7362 | 0.8580 |
|
| 223 |
+
| No log | 3.3398 | 344 | 0.8285 | 0.4607 | 0.8285 | 0.9102 |
|
| 224 |
+
| No log | 3.3592 | 346 | 0.6946 | 0.4978 | 0.6946 | 0.8334 |
|
| 225 |
+
| No log | 3.3786 | 348 | 0.5728 | 0.5655 | 0.5728 | 0.7569 |
|
| 226 |
+
| No log | 3.3981 | 350 | 0.4799 | 0.5873 | 0.4799 | 0.6928 |
|
| 227 |
+
| No log | 3.4175 | 352 | 0.4551 | 0.5620 | 0.4551 | 0.6746 |
|
| 228 |
+
| No log | 3.4369 | 354 | 0.4461 | 0.5751 | 0.4461 | 0.6679 |
|
| 229 |
+
| No log | 3.4563 | 356 | 0.4586 | 0.6076 | 0.4586 | 0.6772 |
|
| 230 |
+
| No log | 3.4757 | 358 | 0.4969 | 0.5935 | 0.4969 | 0.7049 |
|
| 231 |
+
| No log | 3.4951 | 360 | 0.4839 | 0.5918 | 0.4839 | 0.6956 |
|
| 232 |
+
| No log | 3.5146 | 362 | 0.5553 | 0.5848 | 0.5553 | 0.7452 |
|
| 233 |
+
| No log | 3.5340 | 364 | 0.5790 | 0.5699 | 0.5790 | 0.7609 |
|
| 234 |
+
| No log | 3.5534 | 366 | 0.5855 | 0.5619 | 0.5855 | 0.7652 |
|
| 235 |
+
| No log | 3.5728 | 368 | 0.5226 | 0.5843 | 0.5226 | 0.7229 |
|
| 236 |
+
| No log | 3.5922 | 370 | 0.5564 | 0.5770 | 0.5564 | 0.7460 |
|
| 237 |
+
| No log | 3.6117 | 372 | 0.5957 | 0.5599 | 0.5957 | 0.7718 |
|
| 238 |
+
| No log | 3.6311 | 374 | 0.5228 | 0.6219 | 0.5228 | 0.7230 |
|
| 239 |
+
| No log | 3.6505 | 376 | 0.4873 | 0.5599 | 0.4873 | 0.6981 |
|
| 240 |
+
| No log | 3.6699 | 378 | 0.5074 | 0.5823 | 0.5074 | 0.7123 |
|
| 241 |
+
| No log | 3.6893 | 380 | 0.5929 | 0.5690 | 0.5929 | 0.7700 |
|
| 242 |
+
| No log | 3.7087 | 382 | 0.7165 | 0.5651 | 0.7165 | 0.8465 |
|
| 243 |
+
| No log | 3.7282 | 384 | 0.6932 | 0.5776 | 0.6932 | 0.8326 |
|
| 244 |
+
| No log | 3.7476 | 386 | 0.5610 | 0.6242 | 0.5610 | 0.7490 |
|
| 245 |
+
| No log | 3.7670 | 388 | 0.4817 | 0.6541 | 0.4817 | 0.6940 |
|
| 246 |
+
| No log | 3.7864 | 390 | 0.4401 | 0.6346 | 0.4401 | 0.6634 |
|
| 247 |
+
| No log | 3.8058 | 392 | 0.4432 | 0.6213 | 0.4432 | 0.6658 |
|
| 248 |
+
| No log | 3.8252 | 394 | 0.4630 | 0.6454 | 0.4630 | 0.6804 |
|
| 249 |
+
| No log | 3.8447 | 396 | 0.4516 | 0.6545 | 0.4516 | 0.6720 |
|
| 250 |
+
| No log | 3.8641 | 398 | 0.4334 | 0.6349 | 0.4334 | 0.6583 |
|
| 251 |
+
| No log | 3.8835 | 400 | 0.4396 | 0.6147 | 0.4396 | 0.6631 |
|
| 252 |
+
| No log | 3.9029 | 402 | 0.4447 | 0.6368 | 0.4447 | 0.6669 |
|
| 253 |
+
| No log | 3.9223 | 404 | 0.4685 | 0.6367 | 0.4685 | 0.6845 |
|
| 254 |
+
| No log | 3.9417 | 406 | 0.4785 | 0.6309 | 0.4785 | 0.6917 |
|
| 255 |
+
| No log | 3.9612 | 408 | 0.4813 | 0.6193 | 0.4813 | 0.6938 |
|
| 256 |
+
| No log | 3.9806 | 410 | 0.4998 | 0.6362 | 0.4998 | 0.7070 |
|
| 257 |
+
| No log | 4.0 | 412 | 0.4822 | 0.6392 | 0.4822 | 0.6944 |
|
| 258 |
+
| No log | 4.0194 | 414 | 0.4604 | 0.6285 | 0.4604 | 0.6785 |
|
| 259 |
+
| No log | 4.0388 | 416 | 0.4869 | 0.5883 | 0.4869 | 0.6978 |
|
| 260 |
+
| No log | 4.0583 | 418 | 0.5385 | 0.5864 | 0.5385 | 0.7338 |
|
| 261 |
+
| No log | 4.0777 | 420 | 0.4829 | 0.6631 | 0.4829 | 0.6949 |
|
| 262 |
+
| No log | 4.0971 | 422 | 0.4747 | 0.6358 | 0.4747 | 0.6890 |
|
| 263 |
+
| No log | 4.1165 | 424 | 0.5128 | 0.6256 | 0.5128 | 0.7161 |
|
| 264 |
+
| No log | 4.1359 | 426 | 0.5323 | 0.6206 | 0.5323 | 0.7296 |
|
| 265 |
+
| No log | 4.1553 | 428 | 0.5265 | 0.6093 | 0.5265 | 0.7256 |
|
| 266 |
+
| No log | 4.1748 | 430 | 0.5643 | 0.6118 | 0.5643 | 0.7512 |
|
| 267 |
+
| No log | 4.1942 | 432 | 0.6537 | 0.5898 | 0.6537 | 0.8085 |
|
| 268 |
+
| No log | 4.2136 | 434 | 0.5848 | 0.6245 | 0.5848 | 0.7647 |
|
| 269 |
+
| No log | 4.2330 | 436 | 0.4834 | 0.6261 | 0.4834 | 0.6953 |
|
| 270 |
+
| No log | 4.2524 | 438 | 0.4731 | 0.6301 | 0.4731 | 0.6879 |
|
| 271 |
+
| No log | 4.2718 | 440 | 0.4666 | 0.5996 | 0.4666 | 0.6831 |
|
| 272 |
+
| No log | 4.2913 | 442 | 0.4720 | 0.5973 | 0.4720 | 0.6871 |
|
| 273 |
+
| No log | 4.3107 | 444 | 0.4847 | 0.5734 | 0.4847 | 0.6962 |
|
| 274 |
+
| No log | 4.3301 | 446 | 0.5263 | 0.6088 | 0.5263 | 0.7255 |
|
| 275 |
+
| No log | 4.3495 | 448 | 0.6270 | 0.5879 | 0.6270 | 0.7918 |
|
| 276 |
+
| No log | 4.3689 | 450 | 0.6222 | 0.5783 | 0.6222 | 0.7888 |
|
| 277 |
+
| No log | 4.3883 | 452 | 0.5309 | 0.6298 | 0.5309 | 0.7286 |
|
| 278 |
+
| No log | 4.4078 | 454 | 0.4983 | 0.6209 | 0.4983 | 0.7059 |
|
| 279 |
+
| No log | 4.4272 | 456 | 0.4726 | 0.6351 | 0.4726 | 0.6875 |
|
| 280 |
+
| No log | 4.4466 | 458 | 0.5319 | 0.5761 | 0.5319 | 0.7293 |
|
| 281 |
+
| No log | 4.4660 | 460 | 0.5299 | 0.5245 | 0.5299 | 0.7280 |
|
| 282 |
+
| No log | 4.4854 | 462 | 0.5325 | 0.5459 | 0.5325 | 0.7298 |
|
| 283 |
+
| No log | 4.5049 | 464 | 0.5206 | 0.5655 | 0.5206 | 0.7215 |
|
| 284 |
+
| No log | 4.5243 | 466 | 0.5236 | 0.6281 | 0.5236 | 0.7236 |
|
| 285 |
+
| No log | 4.5437 | 468 | 0.6221 | 0.6383 | 0.6221 | 0.7887 |
|
| 286 |
+
| No log | 4.5631 | 470 | 0.9085 | 0.5708 | 0.9085 | 0.9532 |
|
| 287 |
+
| No log | 4.5825 | 472 | 1.0999 | 0.5204 | 1.0999 | 1.0488 |
|
| 288 |
+
| No log | 4.6019 | 474 | 0.9895 | 0.5318 | 0.9895 | 0.9948 |
|
| 289 |
+
| No log | 4.6214 | 476 | 0.7849 | 0.5717 | 0.7849 | 0.8859 |
|
| 290 |
+
| No log | 4.6408 | 478 | 0.6238 | 0.6232 | 0.6238 | 0.7898 |
|
| 291 |
+
| No log | 4.6602 | 480 | 0.5201 | 0.6274 | 0.5201 | 0.7212 |
|
| 292 |
+
| No log | 4.6796 | 482 | 0.5160 | 0.6238 | 0.5160 | 0.7183 |
|
| 293 |
+
| No log | 4.6990 | 484 | 0.5168 | 0.6225 | 0.5168 | 0.7189 |
|
| 294 |
+
| No log | 4.7184 | 486 | 0.4859 | 0.6145 | 0.4859 | 0.6971 |
|
| 295 |
+
| No log | 4.7379 | 488 | 0.4751 | 0.5635 | 0.4751 | 0.6893 |
|
| 296 |
+
| No log | 4.7573 | 490 | 0.4554 | 0.5276 | 0.4554 | 0.6748 |
|
| 297 |
+
| No log | 4.7767 | 492 | 0.4565 | 0.5070 | 0.4565 | 0.6756 |
|
| 298 |
+
| No log | 4.7961 | 494 | 0.4648 | 0.4920 | 0.4648 | 0.6818 |
|
| 299 |
+
| No log | 4.8155 | 496 | 0.4810 | 0.5136 | 0.4810 | 0.6935 |
|
| 300 |
+
| No log | 4.8350 | 498 | 0.5134 | 0.5515 | 0.5134 | 0.7165 |
|
| 301 |
+
| 0.537 | 4.8544 | 500 | 0.5575 | 0.5844 | 0.5575 | 0.7467 |
|
| 302 |
+
| 0.537 | 4.8738 | 502 | 0.5577 | 0.5579 | 0.5577 | 0.7468 |
|
| 303 |
+
| 0.537 | 4.8932 | 504 | 0.5194 | 0.6022 | 0.5194 | 0.7207 |
|
| 304 |
+
| 0.537 | 4.9126 | 506 | 0.4800 | 0.6686 | 0.4800 | 0.6928 |
|
| 305 |
+
| 0.537 | 4.9320 | 508 | 0.4977 | 0.6536 | 0.4977 | 0.7055 |
|
| 306 |
+
| 0.537 | 4.9515 | 510 | 0.5774 | 0.5795 | 0.5774 | 0.7599 |
|
| 307 |
+
| 0.537 | 4.9709 | 512 | 0.7363 | 0.5356 | 0.7363 | 0.8581 |
|
| 308 |
+
| 0.537 | 4.9903 | 514 | 0.7414 | 0.5488 | 0.7414 | 0.8610 |
|
| 309 |
+
| 0.537 | 5.0097 | 516 | 0.7436 | 0.5479 | 0.7436 | 0.8623 |
|
| 310 |
+
| 0.537 | 5.0291 | 518 | 0.6094 | 0.5646 | 0.6094 | 0.7806 |
|
| 311 |
+
|
| 312 |
+
|
| 313 |
+
### Framework versions
|
| 314 |
+
|
| 315 |
+
- Transformers 4.44.2
|
| 316 |
+
- Pytorch 2.4.0+cu118
|
| 317 |
+
- Datasets 2.21.0
|
| 318 |
+
- Tokenizers 0.19.1
|
config.json
ADDED
|
@@ -0,0 +1,32 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "aubmindlab/bert-base-arabertv02",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"BertForSequenceClassification"
|
| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.1,
|
| 7 |
+
"classifier_dropout": null,
|
| 8 |
+
"hidden_act": "gelu",
|
| 9 |
+
"hidden_dropout_prob": 0.1,
|
| 10 |
+
"hidden_size": 768,
|
| 11 |
+
"id2label": {
|
| 12 |
+
"0": "LABEL_0"
|
| 13 |
+
},
|
| 14 |
+
"initializer_range": 0.02,
|
| 15 |
+
"intermediate_size": 3072,
|
| 16 |
+
"label2id": {
|
| 17 |
+
"LABEL_0": 0
|
| 18 |
+
},
|
| 19 |
+
"layer_norm_eps": 1e-12,
|
| 20 |
+
"max_position_embeddings": 512,
|
| 21 |
+
"model_type": "bert",
|
| 22 |
+
"num_attention_heads": 12,
|
| 23 |
+
"num_hidden_layers": 12,
|
| 24 |
+
"pad_token_id": 0,
|
| 25 |
+
"position_embedding_type": "absolute",
|
| 26 |
+
"problem_type": "regression",
|
| 27 |
+
"torch_dtype": "float32",
|
| 28 |
+
"transformers_version": "4.44.2",
|
| 29 |
+
"type_vocab_size": 2,
|
| 30 |
+
"use_cache": true,
|
| 31 |
+
"vocab_size": 64000
|
| 32 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:141ab4a0ab4fbeb5ac2f686d327454d726012132649421623d50cbe3ba6cec28
|
| 3 |
+
size 540799996
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6a38dd55e211eeb82cac7a46674b3c18c26402f726e9a9f48d2e7752981aac5e
|
| 3 |
+
size 5240
|