File size: 2,413 Bytes
8cbc2a8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification_Araieval24_binary_all_data
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# AraBERT_token_classification_Araieval24_binary_all_data
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6550
- Precision: 0.1699
- Recall: 0.2317
- F1: 0.1960
- Accuracy: 0.7589
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4925 | 1.0 | 1495 | 0.5219 | 0.1768 | 0.1444 | 0.1589 | 0.7688 |
| 0.4596 | 2.0 | 2990 | 0.5213 | 0.1275 | 0.1950 | 0.1542 | 0.7560 |
| 0.4273 | 3.0 | 4485 | 0.5231 | 0.1459 | 0.2094 | 0.1720 | 0.7658 |
| 0.4008 | 4.0 | 5980 | 0.5287 | 0.1722 | 0.1925 | 0.1818 | 0.7709 |
| 0.3783 | 5.0 | 7475 | 0.5650 | 0.1667 | 0.2242 | 0.1913 | 0.7646 |
| 0.3592 | 6.0 | 8970 | 0.6256 | 0.1763 | 0.2289 | 0.1992 | 0.7647 |
| 0.3427 | 7.0 | 10465 | 0.6223 | 0.1756 | 0.2256 | 0.1975 | 0.7651 |
| 0.3273 | 8.0 | 11960 | 0.5932 | 0.1691 | 0.2244 | 0.1929 | 0.7608 |
| 0.3199 | 9.0 | 13455 | 0.6602 | 0.1789 | 0.2207 | 0.1976 | 0.7647 |
| 0.3067 | 10.0 | 14950 | 0.6550 | 0.1699 | 0.2317 | 0.1960 | 0.7589 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3
|