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model_15M_small_ds_masking_0.15_predicted_hparamas

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  1. README.md +13 -31
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1261
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- - Accuracy: 0.9546
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  ## Model description
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-------:|:-----:|:---------------:|:--------:|
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- | No log | 0 | 0 | 4.5785 | 0.0163 |
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- | 0.4164 | 0.4302 | 1953 | 0.3256 | 0.8862 |
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- | 0.2809 | 0.8604 | 3906 | 0.2521 | 0.9109 |
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- | 0.2355 | 1.2905 | 5859 | 0.2174 | 0.9226 |
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- | 0.2138 | 1.7207 | 7812 | 0.1972 | 0.9298 |
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- | 0.1987 | 2.1509 | 9765 | 0.1861 | 0.9337 |
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- | 0.188 | 2.5811 | 11718 | 0.1756 | 0.9371 |
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- | 0.1808 | 3.0112 | 13671 | 0.1697 | 0.9397 |
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- | 0.1737 | 3.4414 | 15624 | 0.1638 | 0.9413 |
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- | 0.1686 | 3.8716 | 17577 | 0.1601 | 0.9426 |
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- | 0.1636 | 4.3018 | 19530 | 0.1552 | 0.9444 |
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- | 0.1602 | 4.7319 | 21483 | 0.1525 | 0.9453 |
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- | 0.1567 | 5.1621 | 23436 | 0.1498 | 0.9463 |
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- | 0.1534 | 5.5923 | 25389 | 0.1479 | 0.9466 |
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- | 0.1512 | 6.0225 | 27342 | 0.1445 | 0.9481 |
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- | 0.1499 | 6.4526 | 29295 | 0.1415 | 0.9493 |
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- | 0.1456 | 6.8828 | 31248 | 0.1394 | 0.9500 |
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- | 0.1437 | 7.3130 | 33201 | 0.1382 | 0.9502 |
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- | 0.1427 | 7.7432 | 35154 | 0.1384 | 0.9503 |
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- | 0.1396 | 8.1733 | 37107 | 0.1353 | 0.9514 |
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- | 0.1384 | 8.6035 | 39060 | 0.1330 | 0.9519 |
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- | 0.1371 | 9.0337 | 41013 | 0.1327 | 0.9522 |
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- | 0.1357 | 9.4639 | 42966 | 0.1310 | 0.9528 |
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- | 0.1342 | 9.8941 | 44919 | 0.1286 | 0.9536 |
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- | 0.1312 | 10.3242 | 46872 | 0.1273 | 0.9543 |
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- | 0.132 | 10.7544 | 48825 | 0.1266 | 0.9546 |
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- | 0.1303 | 11.1846 | 50778 | 0.1265 | 0.9546 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2833
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+ - Accuracy: 0.9005
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|
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+ | No log | 0 | 0 | 4.3104 | 0.0009 |
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+ | 0.4317 | 0.4302 | 1953 | 0.3566 | 0.8758 |
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+ | 0.3473 | 0.8604 | 3906 | 0.3130 | 0.8902 |
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+ | 0.3261 | 1.2905 | 5859 | 0.2953 | 0.8964 |
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+ | 0.3179 | 1.7207 | 7812 | 0.2883 | 0.8986 |
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+ | 0.3172 | 2.1509 | 9765 | 0.2873 | 0.8993 |
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+ | 0.3127 | 2.5811 | 11718 | 0.2811 | 0.9016 |
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+ | 0.3235 | 3.0112 | 13671 | 0.2845 | 0.9001 |
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+ | 0.3245 | 3.4414 | 15624 | 0.2907 | 0.8980 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
model.safetensors CHANGED
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