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qa-persian-albert-fa-zwnj-base-v2

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  1. README.md +42 -42
  2. model.safetensors +1 -1
  3. runs/Dec03_00-37-39_Software-AI/events.out.tfevents.1701551259.Software-AI.21828.9 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -17,7 +17,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [makhataei/qa-persian-albert-fa-zwnj-base-v2](https://huggingface.co/makhataei/qa-persian-albert-fa-zwnj-base-v2) on the pquad dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9991
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  ## Model description
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@@ -36,7 +36,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3.90625e-07
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -48,46 +48,46 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:-----:|:---------------:|
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- | 0.0101 | 0.12 | 500 | 2.1486 |
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- | 0.0342 | 0.25 | 1000 | 2.3710 |
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- | 0.1133 | 0.38 | 1500 | 2.3393 |
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- | 0.1976 | 0.5 | 2000 | 2.2309 |
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- | 0.1944 | 0.62 | 2500 | 2.1436 |
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- | 0.2336 | 0.75 | 3000 | 2.0430 |
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- | 0.2277 | 0.88 | 3500 | 1.9529 |
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- | 0.2443 | 1.0 | 4000 | 1.8560 |
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- | 0.1506 | 1.12 | 4500 | 1.8765 |
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- | 0.1369 | 1.25 | 5000 | 1.9003 |
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- | 0.1435 | 1.38 | 5500 | 1.9158 |
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- | 0.1365 | 1.5 | 6000 | 1.9251 |
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- | 0.1387 | 1.62 | 6500 | 1.9243 |
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- | 0.1323 | 1.75 | 7000 | 1.9363 |
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- | 0.1369 | 1.88 | 7500 | 1.9341 |
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- | 0.1312 | 2.0 | 8000 | 1.9389 |
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- | 0.1339 | 2.12 | 8500 | 1.9453 |
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- | 0.1349 | 2.25 | 9000 | 1.9435 |
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- | 0.1418 | 2.38 | 9500 | 1.9479 |
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- | 0.1256 | 2.5 | 10000 | 1.9647 |
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- | 0.1375 | 2.62 | 10500 | 1.9592 |
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- | 0.1237 | 2.75 | 11000 | 1.9647 |
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- | 0.1326 | 2.88 | 11500 | 1.9689 |
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- | 0.126 | 3.0 | 12000 | 1.9736 |
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- | 0.1217 | 3.12 | 12500 | 1.9841 |
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- | 0.1274 | 3.25 | 13000 | 1.9852 |
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- | 0.1285 | 3.38 | 13500 | 1.9878 |
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- | 0.1202 | 3.5 | 14000 | 1.9885 |
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- | 0.1365 | 3.62 | 14500 | 1.9865 |
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- | 0.1319 | 3.75 | 15000 | 1.9847 |
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- | 0.131 | 3.88 | 15500 | 1.9854 |
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- | 0.1258 | 4.0 | 16000 | 1.9887 |
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- | 0.1233 | 4.12 | 16500 | 1.9899 |
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- | 0.1211 | 4.25 | 17000 | 1.9936 |
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- | 0.1326 | 4.38 | 17500 | 1.9935 |
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- | 0.1216 | 4.5 | 18000 | 1.9955 |
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- | 0.1292 | 4.62 | 18500 | 1.9976 |
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- | 0.1166 | 4.75 | 19000 | 1.9982 |
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- | 0.1313 | 4.88 | 19500 | 1.9990 |
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- | 0.1242 | 5.0 | 20000 | 1.9991 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [makhataei/qa-persian-albert-fa-zwnj-base-v2](https://huggingface.co/makhataei/qa-persian-albert-fa-zwnj-base-v2) on the pquad dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.0165
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1.953125e-07
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:-----:|:---------------:|
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+ | 0.0081 | 0.12 | 500 | 2.1432 |
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+ | 0.0312 | 0.25 | 1000 | 2.3066 |
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+ | 0.1035 | 0.38 | 1500 | 2.3197 |
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+ | 0.1844 | 0.5 | 2000 | 2.2733 |
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+ | 0.187 | 0.62 | 2500 | 2.2288 |
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+ | 0.2282 | 0.75 | 3000 | 2.1744 |
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+ | 0.2288 | 0.88 | 3500 | 2.1178 |
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+ | 0.2505 | 1.0 | 4000 | 2.0551 |
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+ | 0.1537 | 1.12 | 4500 | 2.0434 |
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+ | 0.1387 | 1.25 | 5000 | 2.0391 |
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+ | 0.1445 | 1.38 | 5500 | 2.0356 |
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+ | 0.1368 | 1.5 | 6000 | 2.0332 |
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+ | 0.1394 | 1.62 | 6500 | 2.0261 |
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+ | 0.1319 | 1.75 | 7000 | 2.0272 |
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+ | 0.1365 | 1.88 | 7500 | 2.0207 |
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+ | 0.1305 | 2.0 | 8000 | 2.0193 |
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+ | 0.1369 | 2.12 | 8500 | 2.0181 |
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+ | 0.1376 | 2.25 | 9000 | 2.0122 |
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+ | 0.1445 | 2.38 | 9500 | 2.0105 |
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+ | 0.1274 | 2.5 | 10000 | 2.0166 |
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+ | 0.1396 | 2.62 | 10500 | 2.0115 |
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+ | 0.1252 | 2.75 | 11000 | 2.0124 |
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+ | 0.1341 | 2.88 | 11500 | 2.0132 |
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+ | 0.1271 | 3.0 | 12000 | 2.0146 |
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+ | 0.125 | 3.12 | 12500 | 2.0185 |
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+ | 0.1312 | 3.25 | 13000 | 2.0179 |
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+ | 0.1319 | 3.38 | 13500 | 2.0184 |
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+ | 0.1235 | 3.5 | 14000 | 2.0178 |
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+ | 0.1403 | 3.62 | 14500 | 2.0159 |
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+ | 0.1356 | 3.75 | 15000 | 2.0139 |
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+ | 0.1344 | 3.88 | 15500 | 2.0132 |
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+ | 0.1288 | 4.0 | 16000 | 2.0142 |
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+ | 0.1282 | 4.12 | 16500 | 2.0139 |
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+ | 0.1251 | 4.25 | 17000 | 2.0152 |
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+ | 0.1377 | 4.38 | 17500 | 2.0146 |
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+ | 0.1261 | 4.5 | 18000 | 2.0153 |
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+ | 0.134 | 4.62 | 18500 | 2.0160 |
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+ | 0.1205 | 4.75 | 19000 | 2.0162 |
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+ | 0.1359 | 4.88 | 19500 | 2.0165 |
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+ | 0.1289 | 5.0 | 20000 | 2.0165 |
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  ### Framework versions
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