Commit
•
d2406ee
1
Parent(s):
bf02244
Training complete
Browse files
README.md
ADDED
|
@@ -0,0 +1,80 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: qarib/bert-base-qarib60_860k
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- precision
|
| 7 |
+
- recall
|
| 8 |
+
- f1
|
| 9 |
+
- accuracy
|
| 10 |
+
model-index:
|
| 11 |
+
- name: Qarib_arabic_keyword_extraction
|
| 12 |
+
results: []
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 16 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 17 |
+
|
| 18 |
+
# Qarib_arabic_keyword_extraction
|
| 19 |
+
|
| 20 |
+
This model is a fine-tuned version of [qarib/bert-base-qarib60_860k](https://huggingface.co/qarib/bert-base-qarib60_860k) on the None dataset.
|
| 21 |
+
It achieves the following results on the evaluation set:
|
| 22 |
+
- Loss: 0.4027
|
| 23 |
+
- Precision: 0.5369
|
| 24 |
+
- Recall: 0.5937
|
| 25 |
+
- F1: 0.5638
|
| 26 |
+
- Accuracy: 0.9408
|
| 27 |
+
|
| 28 |
+
## Model description
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Intended uses & limitations
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training and evaluation data
|
| 37 |
+
|
| 38 |
+
More information needed
|
| 39 |
+
|
| 40 |
+
## Training procedure
|
| 41 |
+
|
| 42 |
+
### Training hyperparameters
|
| 43 |
+
|
| 44 |
+
The following hyperparameters were used during training:
|
| 45 |
+
- learning_rate: 2e-05
|
| 46 |
+
- train_batch_size: 16
|
| 47 |
+
- eval_batch_size: 8
|
| 48 |
+
- seed: 42
|
| 49 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 50 |
+
- lr_scheduler_type: linear
|
| 51 |
+
- num_epochs: 15
|
| 52 |
+
- mixed_precision_training: Native AMP
|
| 53 |
+
|
| 54 |
+
### Training results
|
| 55 |
+
|
| 56 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 57 |
+
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 58 |
+
| 0.2196 | 1.0 | 750 | 0.1674 | 0.4656 | 0.4190 | 0.4411 | 0.9327 |
|
| 59 |
+
| 0.1374 | 2.0 | 1500 | 0.1559 | 0.4741 | 0.5255 | 0.4985 | 0.9366 |
|
| 60 |
+
| 0.0976 | 3.0 | 2250 | 0.1711 | 0.4901 | 0.5650 | 0.5249 | 0.9378 |
|
| 61 |
+
| 0.0676 | 4.0 | 3000 | 0.1928 | 0.4884 | 0.5557 | 0.5199 | 0.9363 |
|
| 62 |
+
| 0.0474 | 5.0 | 3750 | 0.2109 | 0.5313 | 0.5438 | 0.5375 | 0.9402 |
|
| 63 |
+
| 0.0342 | 6.0 | 4500 | 0.2414 | 0.5259 | 0.5754 | 0.5495 | 0.9389 |
|
| 64 |
+
| 0.024 | 7.0 | 5250 | 0.2527 | 0.5076 | 0.5881 | 0.5449 | 0.9382 |
|
| 65 |
+
| 0.0186 | 8.0 | 6000 | 0.3029 | 0.5379 | 0.5654 | 0.5513 | 0.9400 |
|
| 66 |
+
| 0.0143 | 9.0 | 6750 | 0.3154 | 0.5307 | 0.5862 | 0.5571 | 0.9398 |
|
| 67 |
+
| 0.0108 | 10.0 | 7500 | 0.3490 | 0.5491 | 0.5810 | 0.5646 | 0.9403 |
|
| 68 |
+
| 0.0078 | 11.0 | 8250 | 0.3550 | 0.5475 | 0.5929 | 0.5693 | 0.9412 |
|
| 69 |
+
| 0.0068 | 12.0 | 9000 | 0.3681 | 0.5360 | 0.6019 | 0.5670 | 0.9406 |
|
| 70 |
+
| 0.0049 | 13.0 | 9750 | 0.3873 | 0.5264 | 0.6048 | 0.5629 | 0.9402 |
|
| 71 |
+
| 0.004 | 14.0 | 10500 | 0.3987 | 0.5380 | 0.5937 | 0.5644 | 0.9407 |
|
| 72 |
+
| 0.0034 | 15.0 | 11250 | 0.4027 | 0.5369 | 0.5937 | 0.5638 | 0.9408 |
|
| 73 |
+
|
| 74 |
+
|
| 75 |
+
### Framework versions
|
| 76 |
+
|
| 77 |
+
- Transformers 4.35.2
|
| 78 |
+
- Pytorch 2.1.0+cu121
|
| 79 |
+
- Datasets 2.16.1
|
| 80 |
+
- Tokenizers 0.15.0
|