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Experiment1-system1-roberta-base-finetuned-ner

Token Classification
Transformers
Safetensors
roberta
Generated from Trainer
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  1. README.md +32 -32
  2. model.safetensors +1 -1
  3. tokenizer.json +2 -16
  4. training_args.bin +2 -2
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1871
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- - Precision: 0.9464
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- - Recall: 0.9343
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- - F1: 0.9403
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- - Accuracy: 0.9348
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  ## Model description
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@@ -55,37 +55,37 @@ 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 | 0.04 | 10 | 0.6078 | 0.7957 | 0.8581 | 0.8257 | 0.7957 |
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- | No log | 0.07 | 20 | 0.4732 | 0.7962 | 0.8586 | 0.8262 | 0.7963 |
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- | No log | 0.11 | 30 | 0.3673 | 0.8539 | 0.9005 | 0.8766 | 0.8599 |
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- | No log | 0.15 | 40 | 0.3113 | 0.9100 | 0.8870 | 0.8983 | 0.8868 |
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- | No log | 0.19 | 50 | 0.2817 | 0.8787 | 0.9100 | 0.8941 | 0.8861 |
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- | No log | 0.22 | 60 | 0.2657 | 0.9097 | 0.8975 | 0.9035 | 0.8968 |
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- | No log | 0.26 | 70 | 0.2637 | 0.9322 | 0.8958 | 0.9136 | 0.9043 |
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- | No log | 0.3 | 80 | 0.2278 | 0.9251 | 0.9243 | 0.9247 | 0.9196 |
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- | No log | 0.34 | 90 | 0.2474 | 0.9383 | 0.9011 | 0.9193 | 0.9093 |
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- | No log | 0.37 | 100 | 0.2339 | 0.9233 | 0.9192 | 0.9212 | 0.9174 |
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- | No log | 0.41 | 110 | 0.2312 | 0.9232 | 0.9121 | 0.9176 | 0.9138 |
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- | No log | 0.45 | 120 | 0.2269 | 0.9352 | 0.9133 | 0.9241 | 0.9161 |
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- | No log | 0.49 | 130 | 0.2249 | 0.9348 | 0.9146 | 0.9246 | 0.9178 |
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- | No log | 0.52 | 140 | 0.2086 | 0.9374 | 0.9246 | 0.9310 | 0.9246 |
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- | No log | 0.56 | 150 | 0.2041 | 0.9382 | 0.9280 | 0.9331 | 0.9271 |
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- | No log | 0.6 | 160 | 0.2129 | 0.9414 | 0.9185 | 0.9298 | 0.9238 |
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- | No log | 0.63 | 170 | 0.1960 | 0.9430 | 0.9268 | 0.9349 | 0.9290 |
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- | No log | 0.67 | 180 | 0.1944 | 0.9423 | 0.9277 | 0.9349 | 0.9297 |
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- | No log | 0.71 | 190 | 0.1893 | 0.9445 | 0.9296 | 0.9370 | 0.9319 |
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- | No log | 0.75 | 200 | 0.1900 | 0.9453 | 0.9296 | 0.9374 | 0.9322 |
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- | No log | 0.78 | 210 | 0.1897 | 0.9446 | 0.9321 | 0.9383 | 0.9330 |
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- | No log | 0.82 | 220 | 0.1876 | 0.9451 | 0.9323 | 0.9387 | 0.9334 |
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- | No log | 0.86 | 230 | 0.1913 | 0.9449 | 0.9306 | 0.9377 | 0.9323 |
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- | No log | 0.9 | 240 | 0.1906 | 0.9455 | 0.9308 | 0.9381 | 0.9326 |
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- | No log | 0.93 | 250 | 0.1885 | 0.9456 | 0.9316 | 0.9385 | 0.9331 |
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- | No log | 0.97 | 260 | 0.1870 | 0.9452 | 0.9330 | 0.9390 | 0.9336 |
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  ### Framework versions
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  - Transformers 4.36.2
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- - Pytorch 2.2.1+cu121
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  - Datasets 2.19.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1869
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+ - Precision: 0.9424
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+ - Recall: 0.9335
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+ - F1: 0.9379
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+ - Accuracy: 0.9330
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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 | 0.04 | 10 | 0.6735 | 0.7957 | 0.8581 | 0.8257 | 0.7957 |
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+ | No log | 0.07 | 20 | 0.5323 | 0.7957 | 0.8581 | 0.8257 | 0.7957 |
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+ | No log | 0.11 | 30 | 0.4444 | 0.8146 | 0.8785 | 0.8453 | 0.8146 |
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+ | No log | 0.15 | 40 | 0.3747 | 0.8393 | 0.8973 | 0.8674 | 0.8481 |
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+ | No log | 0.19 | 50 | 0.3110 | 0.8734 | 0.8943 | 0.8837 | 0.8777 |
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+ | No log | 0.22 | 60 | 0.2818 | 0.8934 | 0.9031 | 0.8982 | 0.8906 |
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+ | No log | 0.26 | 70 | 0.2628 | 0.9277 | 0.8946 | 0.9108 | 0.9031 |
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+ | No log | 0.3 | 80 | 0.2407 | 0.9190 | 0.9160 | 0.9175 | 0.9133 |
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+ | No log | 0.34 | 90 | 0.2861 | 0.9285 | 0.8775 | 0.9023 | 0.8883 |
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+ | No log | 0.37 | 100 | 0.2523 | 0.9024 | 0.9150 | 0.9086 | 0.9073 |
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+ | No log | 0.41 | 110 | 0.2351 | 0.9195 | 0.9131 | 0.9163 | 0.9122 |
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+ | No log | 0.45 | 120 | 0.2435 | 0.9339 | 0.9060 | 0.9197 | 0.9111 |
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+ | No log | 0.49 | 130 | 0.2365 | 0.9315 | 0.9097 | 0.9205 | 0.9142 |
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+ | No log | 0.52 | 140 | 0.2182 | 0.9345 | 0.9177 | 0.9260 | 0.9202 |
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+ | No log | 0.56 | 150 | 0.2138 | 0.9355 | 0.9182 | 0.9268 | 0.9207 |
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+ | No log | 0.6 | 160 | 0.2140 | 0.9383 | 0.9187 | 0.9284 | 0.9223 |
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+ | No log | 0.63 | 170 | 0.2018 | 0.9397 | 0.9284 | 0.9340 | 0.9285 |
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+ | No log | 0.67 | 180 | 0.1998 | 0.9408 | 0.9284 | 0.9346 | 0.9290 |
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+ | No log | 0.71 | 190 | 0.1930 | 0.9433 | 0.9292 | 0.9362 | 0.9308 |
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+ | No log | 0.75 | 200 | 0.1908 | 0.9420 | 0.9285 | 0.9352 | 0.9300 |
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+ | No log | 0.78 | 210 | 0.1923 | 0.9392 | 0.9275 | 0.9333 | 0.9279 |
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+ | No log | 0.82 | 220 | 0.1891 | 0.9425 | 0.9297 | 0.9361 | 0.9303 |
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+ | No log | 0.86 | 230 | 0.1877 | 0.9449 | 0.9319 | 0.9384 | 0.9326 |
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+ | No log | 0.9 | 240 | 0.1873 | 0.9448 | 0.9319 | 0.9383 | 0.9323 |
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+ | No log | 0.93 | 250 | 0.1868 | 0.9445 | 0.9328 | 0.9386 | 0.9330 |
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+ | No log | 0.97 | 260 | 0.1866 | 0.9429 | 0.9338 | 0.9383 | 0.9333 |
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  ### Framework versions
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  - Transformers 4.36.2
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+ - Pytorch 1.11.0+cu113
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  - Datasets 2.19.0
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  - Tokenizers 0.15.2
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tokenizer.json CHANGED
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- "pad_token": "<pad>"
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  "added_tokens": [
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