Sfaya-W-Ary-Arz-MSA
This model is a fine-tuned version of CAMeL-Lab/bert-base-arabic-camelbert-da on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0158
- Accuracy: 0.9978
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4027 | 0.1862 | 100 | 0.0415 | 0.9923 |
| 0.0701 | 0.3724 | 200 | 0.0637 | 0.9923 |
| 0.0567 | 0.5587 | 300 | 0.0686 | 0.9945 |
| 0.0365 | 0.7449 | 400 | 0.0605 | 0.9934 |
| 0.036 | 0.9311 | 500 | 0.0351 | 0.9934 |
| 0.0154 | 1.1173 | 600 | 0.0158 | 0.9978 |
| 0.0182 | 1.3035 | 700 | 0.0219 | 0.9967 |
| 0.0235 | 1.4898 | 800 | 0.0956 | 0.9934 |
| 0.0237 | 1.6760 | 900 | 0.0360 | 0.9956 |
| 0.0105 | 1.8622 | 1000 | 0.0240 | 0.9956 |
| 0.0093 | 2.0484 | 1100 | 0.0738 | 0.9934 |
| 0.009 | 2.2346 | 1200 | 0.0278 | 0.9945 |
| 0.0096 | 2.4209 | 1300 | 0.0333 | 0.9956 |
| 0.0164 | 2.6071 | 1400 | 0.0998 | 0.9945 |
| 0.0206 | 2.7933 | 1500 | 0.0747 | 0.9945 |
| 0.0024 | 2.9795 | 1600 | 0.0524 | 0.9912 |
| 0.0002 | 3.1657 | 1700 | 0.1051 | 0.9945 |
| 0.0068 | 3.3520 | 1800 | 0.0264 | 0.9967 |
| 0.0034 | 3.5382 | 1900 | 0.0293 | 0.9945 |
| 0.0087 | 3.7244 | 2000 | 0.0222 | 0.9956 |
| 0.0069 | 3.9106 | 2100 | 0.0305 | 0.9967 |
| 0.0036 | 4.0968 | 2200 | 0.0108 | 0.9967 |
| 0.0025 | 4.2831 | 2300 | 0.0367 | 0.9967 |
| 0.0 | 4.4693 | 2400 | 0.0269 | 0.9967 |
| 0.0044 | 4.6555 | 2500 | 0.0240 | 0.9967 |
| 0.0 | 4.8417 | 2600 | 0.0297 | 0.9967 |
| 0.0 | 5.0279 | 2700 | 0.0608 | 0.9956 |
| 0.0 | 5.2142 | 2800 | 0.0592 | 0.9956 |
| 0.0 | 5.4004 | 2900 | 0.0284 | 0.9967 |
| 0.0 | 5.5866 | 3000 | 0.0285 | 0.9967 |
| 0.0 | 5.7728 | 3100 | 0.0285 | 0.9967 |
| 0.0 | 5.9590 | 3200 | 0.0287 | 0.9967 |
| 0.0016 | 6.1453 | 3300 | 0.0294 | 0.9967 |
| 0.0 | 6.3315 | 3400 | 0.0226 | 0.9978 |
| 0.0 | 6.5177 | 3500 | 0.0227 | 0.9978 |
| 0.0 | 6.7039 | 3600 | 0.0228 | 0.9978 |
| 0.0 | 6.8901 | 3700 | 0.0232 | 0.9978 |
| 0.0 | 7.0764 | 3800 | 0.0233 | 0.9978 |
| 0.0 | 7.2626 | 3900 | 0.0235 | 0.9978 |
| 0.0 | 7.4488 | 4000 | 0.0235 | 0.9978 |
| 0.0 | 7.6350 | 4100 | 0.0235 | 0.9978 |
| 0.0 | 7.8212 | 4200 | 0.0236 | 0.9978 |
| 0.0 | 8.0074 | 4300 | 0.0239 | 0.9978 |
| 0.0 | 8.1937 | 4400 | 0.0240 | 0.9978 |
| 0.0 | 8.3799 | 4500 | 0.0240 | 0.9978 |
| 0.0 | 8.5661 | 4600 | 0.0241 | 0.9978 |
| 0.0 | 8.7523 | 4700 | 0.0241 | 0.9978 |
| 0.0025 | 8.9385 | 4800 | 0.0355 | 0.9934 |
| 0.0 | 9.1248 | 4900 | 0.0310 | 0.9945 |
| 0.0 | 9.3110 | 5000 | 0.0291 | 0.9945 |
| 0.0 | 9.4972 | 5100 | 0.0290 | 0.9956 |
| 0.0 | 9.6834 | 5200 | 0.0290 | 0.9956 |
| 0.0 | 9.8696 | 5300 | 0.0290 | 0.9956 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3