--- base_model: sentence-transformers/all-mpnet-base-v2 library_name: setfit metrics: - accuracy pipeline_tag: text-classification tags: - setfit - sentence-transformers - text-classification - generated_from_setfit_trainer widget: - text: "[brainstorm] Improving `makeseeds.py` \r\nA. Filtering hosts with multiple\ \ ports can be removed IMO:\r\n\r\nhttps://github.com/bitcoin/bitcoin/blob/c44e734dca64a15fae92255a5d848c04adaad2fa/contrib/seeds/makeseeds.py#L215\r\ \n\r\n\r\nB. Tor v3 can also be included in the results.\r\n\r\nC. Recent observation\ \ which can be confirmed with:\r\n\r\n```\r\nwget https://gitlab.com/api/v4/projects/33695681/packages/generic/nrich/0.1.1/nrich_0.1.1_amd64.deb\r\ \nsudo dpkg -i nrich_0.1.1_amd64.deb\r\nhost -t a seed.bitcoin.sipa.be | sed -e\ \ 's/seed.bitcoin.sipa.be has address //g' | nrich -\r\n```\r\n\r\nPossible reasons\ \ for vulnerable machines used for bitcoin nodes:\r\n\r\n1. False positives\r\n\ 2. Users not aware or don't care\r\n3. Attackers prefer using these for better\ \ results\r\n4. Honeypots\r\n5. Other reasons\r\n\r\nLeaving 1 which won't be\ \ true for all the results, filtering such nodes in `makeseeds.py` should make\ \ sense. Below is an example for one IP copied from [`suspicious_hosts.txt`](https://github.com/bitcoin/bitcoin/blob/master/contrib/seeds/suspicious_hosts.txt)\r\ \n\r\n\r\n```python\r\nip = '88.198.17.7'\r\n\r\nurl = 'https://internetdb.shodan.io/'\ \ + ip\r\nresponse = requests.get(url)\r\n\r\nif response.text.find('CVE') !=\ \ -1:\r\n print('vulnerable')\r\n```" - text: Add "walletpassphrasechange" command in bitcoin-wallet.exe This is an underrated useful tool. Dear devs, please add this "feature". Thanks. - text: "qa: Intermittent failure in feature_segwit.py --descriptors https://api.cirrus-ci.com/v1/task/5763159330914304/logs/ci.log\r\ \n```\r\n5/238 - feature_segwit.py --descriptors failed, Duration: 11 s\r\n\r\n\ stdout:\r\n2022-03-16T18:38:33.242000Z TestFramework (INFO): Initializing test\ \ directory /tmp/cirrus-ci-build/ci/scratch/test_runner/test_runner_₿_\U0001F3C3\ _20220316_183814/feature_segwit_225\r\n2022-03-16T18:38:39.177000Z TestFramework\ \ (INFO): Verify sigops are counted in GBT with pre-BIP141 rules before the fork\r\ \n2022-03-16T18:38:43.168000Z TestFramework (INFO): Verify witness txs cannot\ \ be mined before the fork\r\n2022-03-16T18:38:43.200000Z TestFramework (INFO):\ \ Verify unsigned p2sh witness txs without a redeem script are invalid\r\n2022-03-16T18:38:43.630000Z\ \ TestFramework (ERROR): JSONRPC error\r\nTraceback (most recent call last):\r\ \n File \"/tmp/cirrus-ci-build/ci/scratch/build/bitcoin-i686-pc-linux-gnu/test/functional/test_framework/test_framework.py\"\ , line 132, in main\r\n self.run_test()\r\n File \"/tmp/cirrus-ci-build/ci/scratch/build/bitcoin-i686-pc-linux-gnu/test/functional/feature_segwit.py\"\ , line 210, in run_test\r\n self.generate(self.nodes[0], 4) # blocks 428-431\r\ \n File \"/tmp/cirrus-ci-build/ci/scratch/build/bitcoin-i686-pc-linux-gnu/test/functional/test_framework/test_framework.py\"\ , line 639, in generate\r\n blocks = generator.generate(*args, invalid_call=False,\ \ **kwargs)\r\n File \"/tmp/cirrus-ci-build/ci/scratch/build/bitcoin-i686-pc-linux-gnu/test/functional/test_framework/test_node.py\"\ , line 303, in generate\r\n return self.generatetoaddress(nblocks=nblocks,\ \ address=self.get_deterministic_priv_key().address, maxtries=maxtries, **kwargs)\r\ \n File \"/tmp/cirrus-ci-build/ci/scratch/build/bitcoin-i686-pc-linux-gnu/test/functional/test_framework/test_node.py\"\ , line 311, in generatetoaddress\r\n return self.__getattr__('generatetoaddress')(*args,\ \ **kwargs)\r\n File \"/tmp/cirrus-ci-build/ci/scratch/build/bitcoin-i686-pc-linux-gnu/test/functional/test_framework/coverage.py\"\ , line 49, in __call__\r\n return_val = self.auth_service_proxy_instance.__call__(*args,\ \ **kwargs)\r\n File \"/tmp/cirrus-ci-build/ci/scratch/build/bitcoin-i686-pc-linux-gnu/test/functional/test_framework/authproxy.py\"\ , line 144, in __call__\r\n raise JSONRPCException(response['error'], status)\r\ \ntest_framework.authproxy.JSONRPCException: CreateNewBlock: TestBlockValidity\ \ failed: unexpected-witness, ContextualCheckBlock : unexpected witness data found\ \ (-1)\r\n2022-03-16T18:38:43.682000Z TestFramework (INFO): Stopping nodes\r\n\ 2022-03-16T18:38:43.856000Z TestFramework (WARNING): Not cleaning up dir /tmp/cirrus-ci-build/ci/scratch/test_runner/test_runner_₿_\U0001F3C3\ _20220316_183814/feature_segwit_225\r\n2022-03-16T18:38:43.856000Z TestFramework\ \ (ERROR): Test failed. Test logging available at /tmp/cirrus-ci-build/ci/scratch/test_runner/test_runner_₿_\U0001F3C3\ _20220316_183814/feature_segwit_225/test_framework.log\r\n2022-03-16T18:38:43.866000Z\ \ TestFramework (ERROR): \r\n2022-03-16T18:38:43.866000Z TestFramework (ERROR):\ \ Hint: Call /tmp/cirrus-ci-build/ci/scratch/build/bitcoin-i686-pc-linux-gnu/test/functional/combine_logs.py\ \ '/tmp/cirrus-ci-build/ci/scratch/test_runner/test_runner_₿_\U0001F3C3_20220316_183814/feature_segwit_225'\ \ to consolidate all logs\r\n2022-03-16T18:38:43.866000Z TestFramework (ERROR):\ \ \r\n2022-03-16T18:38:43.866000Z TestFramework (ERROR): If this failure happened\ \ unexpectedly or intermittently, please file a bug and provide a link or upload\ \ of the combined log.\r\n2022-03-16T18:38:43.867000Z TestFramework (ERROR): https://github.com/bitcoin/bitcoin/issues\r\ \n2022-03-16T18:38:43.867000Z TestFramework (ERROR): \r\n```" - text: "Rpc not working on 0.17.1 ```\r\ncurl --user test:test --data-binary '{\"\ jsonrpc\": \"1.0\", \"id\":\"curltest\", \"method\": \"getbalance\", \"params\"\ : [\"*\", 1] }' -H 'content-type: text/plain;' http://127.0.0.1:8332/\r\ncurl:\ \ (7) Failed to connect to 127.0.0.1 port 8332: Connection refused\r\n\r\n```\r\ \nBut version 0.16 works " - text: "guix: Prints \"g++: not found\" when building depends Steps to reproduce:\ \ Start a guix build on a system without gcc.\r\n\r\n\r\n```\r\n/bin/sh: 1: gcc:\ \ not found\r\n/bin/sh: 1: gcc: not found\r\n/bin/sh: 1: g++: not found\r\n/bin/sh:\ \ 1: g++: not found\r\nenv: '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends/x86_64-apple-darwin18/native/bin/clang':\ \ No such file or directory\r\nenv: '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends/x86_64-apple-darwin18/native/bin/clang':\ \ No such file or directory\r\nenv: '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends/x86_64-apple-darwin18/native/bin/clang++':\ \ No such file or directory\r\nenv: '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends/x86_64-apple-darwin18/native/bin/clang++':\ \ No such file or directory\r\nFound macOS SDK at '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends/SDKs/Xcode-11.3.1-11C505-extracted-SDK-with-libcxx-headers',\ \ using...\r\nmake: Entering directory '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends'\r\ \n/bin/sh: 1: gcc: not found\r\n/bin/sh: 1: gcc: not found\r\n/bin/sh: 1: g++:\ \ not found\r\n/bin/sh: 1: g++: not found\r\n/bin/sh: 1: gcc: not found\r\n/bin/sh:\ \ 1: gcc: not found\r\n/bin/sh: 1: g++: not found\r\n/bin/sh: 1: g++: not found\r\ \nmake[1]: Entering directory '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends'\r\ \n/bin/sh: 1: gcc: not found\r\n/bin/sh: 1: gcc: not found\r\n/bin/sh: 1: g++:\ \ not found\r\n/bin/sh: 1: g++: not found\r\nenv: '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends/x86_64-apple-darwin/native/bin/clang':\ \ No such file or directory\r\nenv: '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends/x86_64-apple-darwin/native/bin/clang':\ \ No such file or directory\r\nenv: '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends/x86_64-apple-darwin/native/bin/clang++':\ \ No such file or directory\r\nenv: '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends/x86_64-apple-darwin/native/bin/clang++':\ \ No such file or directory\r\nmake[1]: Leaving directory '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends'\r\ \nmake[1]: Entering directory '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends'\r\ \n/bin/sh: 1: gcc: not found\r\n/bin/sh: 1: gcc: not found\r\n/bin/sh: 1: g++:\ \ not found\r\n/bin/sh: 1: g++: not found\r\n/bin/sh: 1: gcc: not found\r\n/bin/sh:\ \ 1: gcc: not found\r\n/bin/sh: 1: g++: not found\r\n/bin/sh: 1: g++: not found\r\ \nmake[1]: Leaving directory '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends'\r\ \nmake[1]: Entering directory '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends'\r\ \n/bin/sh: 1: gcc: not found\r\n/bin/sh: 1: gcc: not found\r\n/bin/sh: 1: g++:\ \ not found\r\n/bin/sh: 1: g++: not found\r\n/bin/sh: 1: x86_64-w64-mingw32-gcc:\ \ not found\r\n/bin/sh: 1: x86_64-w64-mingw32-gcc: not found\r\n/bin/sh: 1: x86_64-w64-mingw32-g++:\ \ not found\r\n/bin/sh: 1: x86_64-w64-mingw32-g++: not found\r\nmake[1]: Leaving\ \ directory '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends'\r\nmake: Leaving\ \ directory '/home/micap/temp/scratch/guix/bitcoin/bitcoin/depends'\r\nINFO: Building\ \ commit a4903f747ccd for platform triple x86_64-linux-gnu:" inference: true --- # SetFit with sentence-transformers/all-mpnet-base-v2 This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Model Details ### Model Description - **Model Type:** SetFit - **Sentence Transformer body:** [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance - **Maximum Sequence Length:** 384 tokens - **Number of Classes:** 3 classes ### Model Sources - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit) - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) ### Model Labels | Label | Examples | 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| bug | | | question | | | feature | | ## Uses ### Direct Use for Inference First install the SetFit library: ```bash pip install setfit ``` Then you can load this model and run inference. ```python from setfit import SetFitModel # Download from the 🤗 Hub model = SetFitModel.from_pretrained("setfit_model_id") # Run inference preds = model("Add \"walletpassphrasechange\" command in bitcoin-wallet.exe This is an underrated useful tool. Dear devs, please add this \"feature\". Thanks.") ``` ## Training Details ### Training Set Metrics | Training set | Min | Median | Max | |:-------------|:----|:---------|:------| | Word count | 2 | 280.1983 | 19599 | | Label | Training Sample Count | |:---------|:----------------------| | bug | 200 | | feature | 200 | | question | 200 | ### Training Hyperparameters - batch_size: (16, 2) - num_epochs: (1, 1) - max_steps: -1 - sampling_strategy: oversampling - num_iterations: 20 - body_learning_rate: (2e-05, 1e-05) - head_learning_rate: 0.01 - loss: CosineSimilarityLoss - distance_metric: cosine_distance - margin: 0.25 - end_to_end: False - use_amp: False - warmup_proportion: 0.1 - seed: 42 - eval_max_steps: -1 - load_best_model_at_end: False ### Training Results | Epoch | Step | Training Loss | Validation Loss | |:------:|:----:|:-------------:|:---------------:| | 0.0007 | 1 | 0.3844 | - | | 0.0067 | 10 | 0.3318 | - | | 0.0133 | 20 | 0.3378 | - | | 0.02 | 30 | 0.2318 | - | | 0.0267 | 40 | 0.2845 | - | | 0.0333 | 50 | 0.2672 | - | | 0.04 | 60 | 0.1494 | - | | 0.0467 | 70 | 0.1949 | - | | 0.0533 | 80 | 0.1737 | - | | 0.06 | 90 | 0.1319 | - | | 0.0667 | 100 | 0.1767 | - | | 0.0733 | 110 | 0.1221 | - | | 0.08 | 120 | 0.1747 | - | | 0.0867 | 130 | 0.1264 | - | | 0.0933 | 140 | 0.1445 | - | | 0.1 | 150 | 0.2189 | - | | 0.1067 | 160 | 0.0893 | - | | 0.1133 | 170 | 0.1636 | - | | 0.12 | 180 | 0.1663 | - | | 0.1267 | 190 | 0.0792 | - | | 0.1333 | 200 | 0.1131 | - | | 0.14 | 210 | 0.1628 | - | | 0.1467 | 220 | 0.1271 | - | | 0.1533 | 230 | 0.175 | - | | 0.16 | 240 | 0.1763 | - | | 0.1667 | 250 | 0.1573 | - | | 0.1733 | 260 | 0.0813 | - | | 0.18 | 270 | 0.1035 | - | | 0.1867 | 280 | 0.0076 | - | | 0.1933 | 290 | 0.2546 | - | | 0.2 | 300 | 0.0526 | - | | 0.2067 | 310 | 0.014 | - | | 0.2133 | 320 | 0.0211 | - | | 0.22 | 330 | 0.0779 | - | | 0.2267 | 340 | 0.0125 | - | | 0.2333 | 350 | 0.0755 | - | | 0.24 | 360 | 0.1108 | - | | 0.2467 | 370 | 0.0351 | - | | 0.2533 | 380 | 0.0096 | - | | 0.26 | 390 | 0.0121 | - | | 0.2667 | 400 | 0.0061 | - | | 0.2733 | 410 | 0.0636 | - | | 0.28 | 420 | 0.071 | - | | 0.2867 | 430 | 0.0024 | - | | 0.2933 | 440 | 0.0082 | - | | 0.3 | 450 | 0.0084 | - | | 0.3067 | 460 | 0.0427 | - | | 0.3133 | 470 | 0.0027 | - | | 0.32 | 480 | 0.0024 | - | | 0.3267 | 490 | 0.001 | - | | 0.3333 | 500 | 0.003 | - | | 0.34 | 510 | 0.0019 | - | | 0.3467 | 520 | 0.0077 | - | | 0.3533 | 530 | 0.0014 | - | | 0.36 | 540 | 0.0024 | - | | 0.3667 | 550 | 0.0008 | - | | 0.3733 | 560 | 0.0011 | - | | 0.38 | 570 | 0.0037 | - | | 0.3867 | 580 | 0.0117 | - | | 0.3933 | 590 | 0.0004 | - | | 0.4 | 600 | 0.0011 | - | | 0.4067 | 610 | 0.0006 | - | | 0.4133 | 620 | 0.0006 | - | | 0.42 | 630 | 0.002 | - | | 0.4267 | 640 | 0.0004 | - | | 0.4333 | 650 | 0.0071 | - | | 0.44 | 660 | 0.0002 | - | | 0.4467 | 670 | 0.0006 | - | | 0.4533 | 680 | 0.0003 | - | | 0.46 | 690 | 0.0003 | - | | 0.4667 | 700 | 0.0002 | - | | 0.4733 | 710 | 0.0002 | - | | 0.48 | 720 | 0.0002 | - | | 0.4867 | 730 | 0.0003 | - | | 0.4933 | 740 | 0.0046 | - | | 0.5 | 750 | 0.0003 | - | | 0.5067 | 760 | 0.0004 | - | | 0.5133 | 770 | 0.0002 | - | | 0.52 | 780 | 0.0003 | - | | 0.5267 | 790 | 0.0001 | - | | 0.5333 | 800 | 0.0002 | - | | 0.54 | 810 | 0.0003 | - | | 0.5467 | 820 | 0.0002 | - | | 0.5533 | 830 | 0.0004 | - | | 0.56 | 840 | 0.0004 | - | | 0.5667 | 850 | 0.0006 | - | | 0.5733 | 860 | 0.0001 | - | | 0.58 | 870 | 0.0002 | - | | 0.5867 | 880 | 0.0002 | - | | 0.5933 | 890 | 0.0001 | - | | 0.6 | 900 | 0.0002 | - | | 0.6067 | 910 | 0.0001 | - | | 0.6133 | 920 | 0.0001 | - | | 0.62 | 930 | 0.0002 | - | | 0.6267 | 940 | 0.0002 | - | | 0.6333 | 950 | 0.0003 | - | | 0.64 | 960 | 0.0498 | - | | 0.6467 | 970 | 0.0002 | - | | 0.6533 | 980 | 0.0001 | - | | 0.66 | 990 | 0.0002 | - | | 0.6667 | 1000 | 0.0002 | - | | 0.6733 | 1010 | 0.0003 | - | | 0.68 | 1020 | 0.0001 | - | | 0.6867 | 1030 | 0.0001 | - | | 0.6933 | 1040 | 0.0001 | - | | 0.7 | 1050 | 0.0001 | - | | 0.7067 | 1060 | 0.0001 | - | | 0.7133 | 1070 | 0.0001 | - | | 0.72 | 1080 | 0.0009 | - | | 0.7267 | 1090 | 0.0001 | - | | 0.7333 | 1100 | 0.044 | - | | 0.74 | 1110 | 0.0001 | - | | 0.7467 | 1120 | 0.0415 | - | | 0.7533 | 1130 | 0.0003 | - | | 0.76 | 1140 | 0.023 | - | | 0.7667 | 1150 | 0.0002 | - | | 0.7733 | 1160 | 0.0001 | - | | 0.78 | 1170 | 0.0004 | - | | 0.7867 | 1180 | 0.0001 | - | | 0.7933 | 1190 | 0.0001 | - | | 0.8 | 1200 | 0.0001 | - | | 0.8067 | 1210 | 0.0001 | - | | 0.8133 | 1220 | 0.0003 | - | | 0.82 | 1230 | 0.0002 | - | | 0.8267 | 1240 | 0.0003 | - | | 0.8333 | 1250 | 0.0001 | - | | 0.84 | 1260 | 0.0001 | - | | 0.8467 | 1270 | 0.0001 | - | | 0.8533 | 1280 | 0.0001 | - | | 0.86 | 1290 | 0.0001 | - | | 0.8667 | 1300 | 0.0001 | - | | 0.8733 | 1310 | 0.0001 | - | | 0.88 | 1320 | 0.0001 | - | | 0.8867 | 1330 | 0.0001 | - | | 0.8933 | 1340 | 0.0001 | - | | 0.9 | 1350 | 0.0001 | - | | 0.9067 | 1360 | 0.0001 | - | | 0.9133 | 1370 | 0.0001 | - | | 0.92 | 1380 | 0.0001 | - | | 0.9267 | 1390 | 0.0001 | - | | 0.9333 | 1400 | 0.0003 | - | | 0.94 | 1410 | 0.0001 | - | | 0.9467 | 1420 | 0.0001 | - | | 0.9533 | 1430 | 0.0001 | - | | 0.96 | 1440 | 0.0001 | - | | 0.9667 | 1450 | 0.0002 | - | | 0.9733 | 1460 | 0.0003 | - | | 0.98 | 1470 | 0.0002 | - | | 0.9867 | 1480 | 0.0002 | - | | 0.9933 | 1490 | 0.0001 | - | | 1.0 | 1500 | 0.0195 | - | ### Framework Versions - Python: 3.10.12 - SetFit: 1.0.3 - Sentence Transformers: 3.0.1 - Transformers: 4.39.0 - PyTorch: 2.3.0+cu121 - Datasets: 2.20.0 - Tokenizers: 0.15.2 ## Citation ### BibTeX ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ```