Downloads · 30 days
6
29% of all-time downloads
MayBashendy/Arabic_FineTuningAraBERT_noAug_task3_organization_fold1
Arabic_FineTuningAraBERT_noAug_task3_organization_fold1 is a text classification model from MayBashendy. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
6
29% of all-time downloads
All-time downloads
21
Public
Parameters
135M
1.1 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors541 MB · 100%
From the Hugging Face model README
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|---|---|---|---|---|---|---|
| No log | 0.3333 | 2 | 4.3037 | 0.0153 | 4.3037 | 2.0745 |
| No log | 0.6667 | 4 | 2.2464 | 0.0 | 2.2464 | 1.4988 |
| No log | 1.0 | 6 | 1.0081 | -0.0168 | 1.0081 | 1.0040 |
| No log | 1.3333 | 8 | 0.6535 | 0.0253 | 0.6535 | 0.8084 |
| No log | 1.6667 | 10 | 0.8673 | 0.0120 | 0.8673 | 0.9313 |
| No log | 2.0 | 12 | 0.7327 | 0.0120 | 0.7327 | 0.8560 |
| No log | 2.3333 | 14 | 0.7943 | 0.0120 | 0.7943 | 0.8912 |
| No log | 2.6667 | 16 | 0.8708 | 0.0 | 0.8708 | 0.9332 |
| No log | 3.0 | 18 | 0.7803 | 0.0 | 0.7803 | 0.8834 |
| No log | 3.3333 | 20 | 0.6282 | 0.0120 | 0.6282 | 0.7926 |
| No log | 3.6667 | 22 | 0.5509 | 0.2143 | 0.5509 | 0.7423 |
| No log | 4.0 | 24 | 0.5582 | 0.2443 | 0.5582 | 0.7471 |
| No log | 4.3333 | 26 | 0.5330 | 0.2143 | 0.5330 | 0.7301 |
| No log | 4.6667 | 28 | 0.5411 | 0.1646 | 0.5411 | 0.7356 |
| No log | 5.0 | 30 | 0.5874 | 0.0 | 0.5874 | 0.7664 |
| No log | 5.3333 | 32 | 0.6514 | 0.0 | 0.6514 | 0.8071 |
| No log | 5.6667 | 34 | 0.7315 | 0.0 | 0.7315 | 0.8553 |
| No log | 6.0 | 36 | 0.7363 | 0.0 | 0.7363 | 0.8581 |
| No log | 6.3333 | 38 | 0.6468 | 0.0120 | 0.6468 | 0.8042 |
| No log | 6.6667 | 40 | 0.5834 | 0.0120 | 0.5834 | 0.7638 |
| No log | 7.0 | 42 | 0.5718 | 0.0120 | 0.5718 | 0.7561 |
| No log | 7.3333 | 44 | 0.5732 | 0.0120 | 0.5732 | 0.7571 |
| No log | 7.6667 | 46 | 0.5866 | 0.0120 | 0.5866 | 0.7659 |
| No log | 8.0 | 48 | 0.5980 | 0.0120 | 0.5980 | 0.7733 |
| No log | 8.3333 | 50 | 0.6420 | 0.0120 | 0.6420 | 0.8012 |
| No log | 8.6667 | 52 | 0.6888 | 0.0120 | 0.6888 | 0.8299 |
| No log | 9.0 | 54 | 0.6809 | 0.0120 | 0.6809 | 0.8252 |
| No log | 9.3333 | 56 | 0.6553 | 0.0120 | 0.6553 | 0.8095 |
| No log | 9.6667 | 58 | 0.6276 | 0.0120 | 0.6276 | 0.7922 |
| No log | 10.0 | 60 | 0.6174 | 0.0120 | 0.6174 | 0.7858 |