--- library_name: transformers license: mit base_model: FacebookAI/roberta-base tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: roberta-base-finetuned-ner results: [] --- # roberta-base-finetuned-ner This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9020 - Precision: 0.6105 - Recall: 0.6545 - F1: 0.6317 - Accuracy: 0.8984 ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 60 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 63 | 0.7317 | 0.6254 | 0.6378 | 0.6315 | 0.9019 | | No log | 2.0 | 126 | 0.7668 | 0.6130 | 0.6482 | 0.6301 | 0.9 | | No log | 3.0 | 189 | 0.7691 | 0.6123 | 0.6545 | 0.6327 | 0.8992 | | No log | 4.0 | 252 | 0.7907 | 0.6061 | 0.6232 | 0.6145 | 0.8956 | | No log | 5.0 | 315 | 0.8165 | 0.5798 | 0.6482 | 0.6121 | 0.8957 | | No log | 6.0 | 378 | 0.7758 | 0.6008 | 0.6534 | 0.6260 | 0.8999 | | No log | 7.0 | 441 | 0.8109 | 0.6018 | 0.6357 | 0.6183 | 0.8984 | | 0.0018 | 8.0 | 504 | 0.7892 | 0.6018 | 0.6388 | 0.6197 | 0.8992 | | 0.0018 | 9.0 | 567 | 0.8051 | 0.5878 | 0.6461 | 0.6156 | 0.8964 | | 0.0018 | 10.0 | 630 | 0.7913 | 0.6123 | 0.6430 | 0.6273 | 0.8999 | | 0.0018 | 11.0 | 693 | 0.8088 | 0.6012 | 0.6545 | 0.6267 | 0.8979 | | 0.0018 | 12.0 | 756 | 0.8206 | 0.6072 | 0.6534 | 0.6295 | 0.8974 | | 0.0018 | 13.0 | 819 | 0.8240 | 0.5858 | 0.6482 | 0.6155 | 0.8962 | | 0.0018 | 14.0 | 882 | 0.8369 | 0.5961 | 0.6409 | 0.6177 | 0.8971 | | 0.0018 | 15.0 | 945 | 0.8515 | 0.5951 | 0.6367 | 0.6152 | 0.8960 | | 0.0012 | 16.0 | 1008 | 0.8743 | 0.5881 | 0.6096 | 0.5987 | 0.8949 | | 0.0012 | 17.0 | 1071 | 0.8835 | 0.5945 | 0.6336 | 0.6134 | 0.8960 | | 0.0012 | 18.0 | 1134 | 0.8633 | 0.5803 | 0.6409 | 0.6091 | 0.8946 | | 0.0012 | 19.0 | 1197 | 0.8553 | 0.5899 | 0.6127 | 0.6011 | 0.8942 | | 0.0012 | 20.0 | 1260 | 0.8715 | 0.5841 | 0.6232 | 0.6030 | 0.8938 | | 0.0012 | 21.0 | 1323 | 0.8922 | 0.5881 | 0.6305 | 0.6086 | 0.8909 | | 0.0012 | 22.0 | 1386 | 0.8716 | 0.5926 | 0.6482 | 0.6191 | 0.8935 | | 0.0012 | 23.0 | 1449 | 0.8853 | 0.5915 | 0.6545 | 0.6214 | 0.8942 | | 0.0008 | 24.0 | 1512 | 0.8494 | 0.6132 | 0.6388 | 0.6258 | 0.8973 | | 0.0008 | 25.0 | 1575 | 0.8698 | 0.5901 | 0.6461 | 0.6168 | 0.8937 | | 0.0008 | 26.0 | 1638 | 0.8622 | 0.5996 | 0.6409 | 0.6196 | 0.8946 | | 0.0008 | 27.0 | 1701 | 0.8517 | 0.6057 | 0.6430 | 0.6238 | 0.8970 | | 0.0008 | 28.0 | 1764 | 0.8696 | 0.6108 | 0.6388 | 0.6245 | 0.8977 | | 0.0008 | 29.0 | 1827 | 0.8753 | 0.5979 | 0.6503 | 0.6230 | 0.8978 | | 0.0008 | 30.0 | 1890 | 0.8519 | 0.6026 | 0.6409 | 0.6211 | 0.8973 | | 0.0008 | 31.0 | 1953 | 0.8588 | 0.6086 | 0.6524 | 0.6297 | 0.8992 | | 0.0007 | 32.0 | 2016 | 0.8713 | 0.5968 | 0.6305 | 0.6132 | 0.8970 | | 0.0007 | 33.0 | 2079 | 0.8761 | 0.5982 | 0.6388 | 0.6179 | 0.8975 | | 0.0007 | 34.0 | 2142 | 0.8733 | 0.5947 | 0.6357 | 0.6145 | 0.8967 | | 0.0007 | 35.0 | 2205 | 0.8793 | 0.5996 | 0.6378 | 0.6181 | 0.8977 | | 0.0007 | 36.0 | 2268 | 0.8959 | 0.5950 | 0.6503 | 0.6214 | 0.8971 | | 0.0007 | 37.0 | 2331 | 0.8795 | 0.6078 | 0.6534 | 0.6298 | 0.8986 | | 0.0007 | 38.0 | 2394 | 0.8856 | 0.6208 | 0.6597 | 0.6397 | 0.9 | | 0.0007 | 39.0 | 2457 | 0.8897 | 0.6155 | 0.6534 | 0.6339 | 0.8992 | | 0.0005 | 40.0 | 2520 | 0.8901 | 0.6098 | 0.6524 | 0.6304 | 0.8988 | | 0.0005 | 41.0 | 2583 | 0.8881 | 0.6142 | 0.6482 | 0.6308 | 0.8984 | | 0.0005 | 42.0 | 2646 | 0.8857 | 0.6193 | 0.6503 | 0.6344 | 0.8989 | | 0.0005 | 43.0 | 2709 | 0.8911 | 0.6121 | 0.6524 | 0.6316 | 0.8973 | | 0.0005 | 44.0 | 2772 | 0.8988 | 0.6015 | 0.6493 | 0.6245 | 0.8968 | | 0.0005 | 45.0 | 2835 | 0.8927 | 0.6169 | 0.6472 | 0.6317 | 0.8978 | | 0.0005 | 46.0 | 2898 | 0.8974 | 0.6137 | 0.6649 | 0.6383 | 0.8978 | | 0.0005 | 47.0 | 2961 | 0.8991 | 0.6115 | 0.6555 | 0.6327 | 0.8968 | | 0.0004 | 48.0 | 3024 | 0.9001 | 0.6087 | 0.6545 | 0.6308 | 0.8966 | | 0.0004 | 49.0 | 3087 | 0.9015 | 0.6071 | 0.6566 | 0.6309 | 0.8968 | | 0.0004 | 50.0 | 3150 | 0.8986 | 0.6109 | 0.6524 | 0.6310 | 0.8968 | | 0.0004 | 51.0 | 3213 | 0.9014 | 0.6083 | 0.6597 | 0.6329 | 0.8984 | | 0.0004 | 52.0 | 3276 | 0.9018 | 0.6091 | 0.6587 | 0.6329 | 0.8988 | | 0.0004 | 53.0 | 3339 | 0.8991 | 0.6107 | 0.6534 | 0.6314 | 0.8986 | | 0.0004 | 54.0 | 3402 | 0.9000 | 0.6084 | 0.6534 | 0.6301 | 0.8985 | | 0.0004 | 55.0 | 3465 | 0.9015 | 0.6081 | 0.6545 | 0.6305 | 0.8988 | | 0.0003 | 56.0 | 3528 | 0.9019 | 0.6054 | 0.6503 | 0.6271 | 0.8982 | | 0.0003 | 57.0 | 3591 | 0.9011 | 0.6086 | 0.6524 | 0.6297 | 0.8982 | | 0.0003 | 58.0 | 3654 | 0.9017 | 0.6080 | 0.6524 | 0.6294 | 0.8984 | | 0.0003 | 59.0 | 3717 | 0.9019 | 0.6121 | 0.6555 | 0.6331 | 0.8985 | | 0.0003 | 60.0 | 3780 | 0.9020 | 0.6105 | 0.6545 | 0.6317 | 0.8984 | ### Framework versions - Transformers 4.45.2 - Pytorch 2.4.1 - Datasets 2.18.0 - Tokenizers 0.20.0