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bert-base-spanish-wwm-uncased-finetuned-clinical

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+ ---
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: bert-base-spanish-wwm-uncased-finetuned-clinical
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # bert-base-spanish-wwm-uncased-finetuned-clinical
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+
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+ This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7962
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+ - F1: 0.1081
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 80
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:------:|:---------------:|:------:|
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+ | 1.1202 | 1.0 | 2007 | 1.0018 | 0.0062 |
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+ | 1.0153 | 2.0 | 4014 | 0.9376 | 0.0166 |
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+ | 0.9779 | 3.0 | 6021 | 0.9026 | 0.0342 |
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+ | 0.9598 | 4.0 | 8028 | 0.8879 | 0.0337 |
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+ | 0.9454 | 5.0 | 10035 | 0.8699 | 0.0598 |
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+ | 0.9334 | 6.0 | 12042 | 0.8546 | 0.0682 |
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+ | 0.9263 | 7.0 | 14049 | 0.8533 | 0.0551 |
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+ | 0.9279 | 8.0 | 16056 | 0.8538 | 0.0715 |
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+ | 0.9184 | 9.0 | 18063 | 0.8512 | 0.0652 |
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+ | 0.9151 | 10.0 | 20070 | 0.8313 | 0.0789 |
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+ | 0.9092 | 11.0 | 22077 | 0.8299 | 0.0838 |
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+ | 0.9083 | 12.0 | 24084 | 0.8331 | 0.0718 |
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+ | 0.9057 | 13.0 | 26091 | 0.8319 | 0.0719 |
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+ | 0.9018 | 14.0 | 28098 | 0.8133 | 0.0969 |
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+ | 0.9068 | 15.0 | 30105 | 0.8234 | 0.0816 |
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+ | 0.9034 | 16.0 | 32112 | 0.8151 | 0.0899 |
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+ | 0.9008 | 17.0 | 34119 | 0.8145 | 0.0967 |
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+ | 0.8977 | 18.0 | 36126 | 0.8168 | 0.0891 |
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+ | 0.898 | 19.0 | 38133 | 0.8167 | 0.0818 |
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+ | 0.8956 | 20.0 | 40140 | 0.8076 | 0.1030 |
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+ | 0.8983 | 21.0 | 42147 | 0.8129 | 0.0867 |
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+ | 0.896 | 22.0 | 44154 | 0.8118 | 0.0892 |
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+ | 0.8962 | 23.0 | 46161 | 0.8066 | 0.1017 |
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+ | 0.8917 | 24.0 | 48168 | 0.8154 | 0.0908 |
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+ | 0.8923 | 25.0 | 50175 | 0.8154 | 0.0897 |
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+ | 0.8976 | 26.0 | 52182 | 0.8089 | 0.0910 |
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+ | 0.8926 | 27.0 | 54189 | 0.8069 | 0.0947 |
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+ | 0.8911 | 28.0 | 56196 | 0.8170 | 0.0882 |
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+ | 0.8901 | 29.0 | 58203 | 0.7991 | 0.1112 |
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+ | 0.8934 | 30.0 | 60210 | 0.7996 | 0.1112 |
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+ | 0.8903 | 31.0 | 62217 | 0.8049 | 0.0950 |
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+ | 0.8924 | 32.0 | 64224 | 0.8116 | 0.0951 |
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+ | 0.8887 | 33.0 | 66231 | 0.7982 | 0.1075 |
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+ | 0.8922 | 34.0 | 68238 | 0.8013 | 0.1025 |
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+ | 0.8871 | 35.0 | 70245 | 0.8064 | 0.0979 |
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+ | 0.8913 | 36.0 | 72252 | 0.8108 | 0.0909 |
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+ | 0.8924 | 37.0 | 74259 | 0.8081 | 0.0889 |
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+ | 0.8848 | 38.0 | 76266 | 0.7923 | 0.1228 |
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+ | 0.8892 | 39.0 | 78273 | 0.8025 | 0.0959 |
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+ | 0.8886 | 40.0 | 80280 | 0.7954 | 0.1148 |
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+ | 0.8938 | 41.0 | 82287 | 0.8017 | 0.1058 |
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+ | 0.8897 | 42.0 | 84294 | 0.7946 | 0.1146 |
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+ | 0.8906 | 43.0 | 86301 | 0.7983 | 0.1102 |
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+ | 0.889 | 44.0 | 88308 | 0.8068 | 0.0950 |
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+ | 0.8872 | 45.0 | 90315 | 0.7999 | 0.1089 |
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+ | 0.8902 | 46.0 | 92322 | 0.7992 | 0.0999 |
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+ | 0.8912 | 47.0 | 94329 | 0.7981 | 0.1048 |
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+ | 0.886 | 48.0 | 96336 | 0.8024 | 0.0991 |
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+ | 0.8848 | 49.0 | 98343 | 0.8026 | 0.0984 |
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+ | 0.8866 | 50.0 | 100350 | 0.7965 | 0.1135 |
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+ | 0.8848 | 51.0 | 102357 | 0.8054 | 0.0926 |
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+ | 0.8863 | 52.0 | 104364 | 0.8068 | 0.0917 |
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+ | 0.8866 | 53.0 | 106371 | 0.7993 | 0.0964 |
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+ | 0.8823 | 54.0 | 108378 | 0.7929 | 0.1126 |
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+ | 0.8911 | 55.0 | 110385 | 0.7938 | 0.1132 |
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+ | 0.8911 | 56.0 | 112392 | 0.7932 | 0.1144 |
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+ | 0.8866 | 57.0 | 114399 | 0.8018 | 0.0957 |
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+ | 0.8841 | 58.0 | 116406 | 0.7976 | 0.1015 |
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+ | 0.8874 | 59.0 | 118413 | 0.8035 | 0.0966 |
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+ | 0.887 | 60.0 | 120420 | 0.7954 | 0.1112 |
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+ | 0.888 | 61.0 | 122427 | 0.7927 | 0.1164 |
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+ | 0.8845 | 62.0 | 124434 | 0.7982 | 0.1012 |
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+ | 0.8848 | 63.0 | 126441 | 0.7978 | 0.1034 |
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+ | 0.8857 | 64.0 | 128448 | 0.8036 | 0.0969 |
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+ | 0.8827 | 65.0 | 130455 | 0.7958 | 0.1036 |
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+ | 0.8878 | 66.0 | 132462 | 0.7983 | 0.1030 |
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+ | 0.885 | 67.0 | 134469 | 0.7956 | 0.1055 |
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+ | 0.8859 | 68.0 | 136476 | 0.7964 | 0.1058 |
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+ | 0.8872 | 69.0 | 138483 | 0.7989 | 0.1005 |
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+ | 0.8841 | 70.0 | 140490 | 0.7949 | 0.1138 |
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+ | 0.8846 | 71.0 | 142497 | 0.7960 | 0.1062 |
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+ | 0.8867 | 72.0 | 144504 | 0.7965 | 0.1058 |
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+ | 0.8856 | 73.0 | 146511 | 0.7980 | 0.1007 |
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+ | 0.8852 | 74.0 | 148518 | 0.7971 | 0.1012 |
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+ | 0.8841 | 75.0 | 150525 | 0.7975 | 0.1049 |
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+ | 0.8865 | 76.0 | 152532 | 0.7981 | 0.1010 |
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+ | 0.8887 | 77.0 | 154539 | 0.7945 | 0.1095 |
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+ | 0.8853 | 78.0 | 156546 | 0.7965 | 0.1053 |
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+ | 0.8843 | 79.0 | 158553 | 0.7966 | 0.1062 |
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+ | 0.8858 | 80.0 | 160560 | 0.7962 | 0.1081 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.20.1
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+ - Pytorch 1.9.0+cu102
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+ - Datasets 2.3.2
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+ - Tokenizers 0.12.1