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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2165
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- - Precision: 0.4553
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- - Recall: 0.6087
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- - F1: 0.5209
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- - Accuracy: 0.9624
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  ## Model description
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@@ -54,36 +54,36 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 57 | 0.2201 | 0.0 | 0.0 | 0.0 | 0.9516 |
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- | No log | 2.0 | 114 | 0.1915 | 0.0 | 0.0 | 0.0 | 0.9530 |
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- | No log | 3.0 | 171 | 0.1680 | 0.2429 | 0.0924 | 0.1339 | 0.9528 |
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- | No log | 4.0 | 228 | 0.1471 | 0.3516 | 0.2446 | 0.2885 | 0.9560 |
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- | No log | 5.0 | 285 | 0.1473 | 0.3056 | 0.2989 | 0.3022 | 0.9548 |
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- | No log | 6.0 | 342 | 0.1376 | 0.3937 | 0.3424 | 0.3663 | 0.9595 |
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- | No log | 7.0 | 399 | 0.1431 | 0.3875 | 0.5054 | 0.4387 | 0.9580 |
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- | No log | 8.0 | 456 | 0.1573 | 0.4364 | 0.5598 | 0.4905 | 0.9592 |
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- | 0.1396 | 9.0 | 513 | 0.1442 | 0.4794 | 0.5054 | 0.4921 | 0.9648 |
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- | 0.1396 | 10.0 | 570 | 0.1908 | 0.3820 | 0.6685 | 0.4862 | 0.9525 |
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- | 0.1396 | 11.0 | 627 | 0.1552 | 0.4516 | 0.6087 | 0.5185 | 0.9624 |
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- | 0.1396 | 12.0 | 684 | 0.1834 | 0.444 | 0.6033 | 0.5115 | 0.9614 |
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- | 0.1396 | 13.0 | 741 | 0.1669 | 0.4810 | 0.6196 | 0.5416 | 0.9634 |
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- | 0.1396 | 14.0 | 798 | 0.1854 | 0.4582 | 0.625 | 0.5287 | 0.9629 |
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- | 0.1396 | 15.0 | 855 | 0.2204 | 0.3859 | 0.6522 | 0.4848 | 0.9525 |
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- | 0.1396 | 16.0 | 912 | 0.2062 | 0.4221 | 0.6033 | 0.4966 | 0.9577 |
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- | 0.1396 | 17.0 | 969 | 0.1928 | 0.4596 | 0.5870 | 0.5155 | 0.9639 |
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- | 0.0141 | 18.0 | 1026 | 0.2061 | 0.4531 | 0.6033 | 0.5175 | 0.9619 |
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- | 0.0141 | 19.0 | 1083 | 0.2036 | 0.4464 | 0.5652 | 0.4988 | 0.9621 |
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- | 0.0141 | 20.0 | 1140 | 0.2110 | 0.4557 | 0.5870 | 0.5131 | 0.9627 |
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- | 0.0141 | 21.0 | 1197 | 0.2115 | 0.4462 | 0.6087 | 0.5149 | 0.9616 |
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- | 0.0141 | 22.0 | 1254 | 0.2176 | 0.4488 | 0.6196 | 0.5205 | 0.9619 |
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- | 0.0141 | 23.0 | 1311 | 0.2180 | 0.4427 | 0.6304 | 0.5202 | 0.9609 |
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- | 0.0141 | 24.0 | 1368 | 0.2162 | 0.4578 | 0.6196 | 0.5266 | 0.9624 |
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- | 0.0141 | 25.0 | 1425 | 0.2218 | 0.4394 | 0.6304 | 0.5179 | 0.9604 |
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- | 0.0141 | 26.0 | 1482 | 0.2151 | 0.4585 | 0.6304 | 0.5309 | 0.9629 |
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- | 0.003 | 27.0 | 1539 | 0.2163 | 0.4597 | 0.6196 | 0.5278 | 0.9627 |
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- | 0.003 | 28.0 | 1596 | 0.2174 | 0.456 | 0.6196 | 0.5253 | 0.9624 |
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- | 0.003 | 29.0 | 1653 | 0.2147 | 0.4545 | 0.5978 | 0.5164 | 0.9626 |
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- | 0.003 | 30.0 | 1710 | 0.2165 | 0.4553 | 0.6087 | 0.5209 | 0.9624 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2031
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+ - Precision: 0.5065
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+ - Recall: 0.6359
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+ - F1: 0.5639
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+ - Accuracy: 0.9658
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 57 | 0.2133 | 0.0 | 0.0 | 0.0 | 0.9516 |
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+ | No log | 2.0 | 114 | 0.1757 | 0.2 | 0.0163 | 0.0302 | 0.9550 |
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+ | No log | 3.0 | 171 | 0.1591 | 0.2893 | 0.1902 | 0.2295 | 0.9535 |
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+ | No log | 4.0 | 228 | 0.1386 | 0.3433 | 0.25 | 0.2893 | 0.9582 |
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+ | No log | 5.0 | 285 | 0.1349 | 0.4345 | 0.3967 | 0.4148 | 0.9600 |
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+ | No log | 6.0 | 342 | 0.1311 | 0.5352 | 0.4130 | 0.4663 | 0.9646 |
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+ | No log | 7.0 | 399 | 0.1402 | 0.4264 | 0.5978 | 0.4977 | 0.9590 |
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+ | No log | 8.0 | 456 | 0.1377 | 0.4858 | 0.5598 | 0.5202 | 0.9634 |
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+ | 0.1282 | 9.0 | 513 | 0.1539 | 0.5226 | 0.4402 | 0.4779 | 0.9651 |
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+ | 0.1282 | 10.0 | 570 | 0.1631 | 0.4597 | 0.6196 | 0.5278 | 0.9607 |
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+ | 0.1282 | 11.0 | 627 | 0.1511 | 0.5333 | 0.4783 | 0.5043 | 0.9666 |
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+ | 0.1282 | 12.0 | 684 | 0.1705 | 0.4690 | 0.5761 | 0.5171 | 0.9626 |
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+ | 0.1282 | 13.0 | 741 | 0.1760 | 0.5138 | 0.5054 | 0.5096 | 0.9651 |
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+ | 0.1282 | 14.0 | 798 | 0.1917 | 0.4296 | 0.6630 | 0.5214 | 0.9580 |
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+ | 0.1282 | 15.0 | 855 | 0.1833 | 0.4563 | 0.625 | 0.5275 | 0.9619 |
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+ | 0.1282 | 16.0 | 912 | 0.1887 | 0.4933 | 0.6033 | 0.5428 | 0.9638 |
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+ | 0.1282 | 17.0 | 969 | 0.1723 | 0.5138 | 0.6087 | 0.5572 | 0.9659 |
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+ | 0.0102 | 18.0 | 1026 | 0.1849 | 0.5022 | 0.6196 | 0.5547 | 0.9649 |
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+ | 0.0102 | 19.0 | 1083 | 0.1773 | 0.5352 | 0.6196 | 0.5743 | 0.9676 |
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+ | 0.0102 | 20.0 | 1140 | 0.1945 | 0.4957 | 0.6304 | 0.5550 | 0.9646 |
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+ | 0.0102 | 21.0 | 1197 | 0.1967 | 0.4756 | 0.6359 | 0.5442 | 0.9634 |
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+ | 0.0102 | 22.0 | 1254 | 0.1876 | 0.4978 | 0.6087 | 0.5477 | 0.9658 |
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+ | 0.0102 | 23.0 | 1311 | 0.1935 | 0.4978 | 0.6087 | 0.5477 | 0.9656 |
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+ | 0.0102 | 24.0 | 1368 | 0.1930 | 0.5256 | 0.6141 | 0.5664 | 0.9671 |
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+ | 0.0102 | 25.0 | 1425 | 0.1945 | 0.5110 | 0.6304 | 0.5645 | 0.9661 |
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+ | 0.0102 | 26.0 | 1482 | 0.1955 | 0.5283 | 0.6087 | 0.5657 | 0.9673 |
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+ | 0.0023 | 27.0 | 1539 | 0.2017 | 0.5043 | 0.6359 | 0.5625 | 0.9654 |
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+ | 0.0023 | 28.0 | 1596 | 0.2010 | 0.5088 | 0.6304 | 0.5631 | 0.9659 |
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+ | 0.0023 | 29.0 | 1653 | 0.2019 | 0.5088 | 0.6304 | 0.5631 | 0.9659 |
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+ | 0.0023 | 30.0 | 1710 | 0.2031 | 0.5065 | 0.6359 | 0.5639 | 0.9658 |
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  ### Framework versions