Instructions to use xXiaobuding/deberta-v3-base_ai4privacy_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xXiaobuding/deberta-v3-base_ai4privacy_en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="xXiaobuding/deberta-v3-base_ai4privacy_en")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("xXiaobuding/deberta-v3-base_ai4privacy_en") model = AutoModelForTokenClassification.from_pretrained("xXiaobuding/deberta-v3-base_ai4privacy_en") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "eval_ACCOUNTNAME_f1": 0.9898477157360406, | |
| "eval_ACCOUNTNUMBER_f1": 0.9939393939393939, | |
| "eval_AGE_f1": 0.8396946564885497, | |
| "eval_AMOUNT_f1": 0.9169381107491856, | |
| "eval_BIC_f1": 0.9011627906976744, | |
| "eval_BITCOINADDRESS_f1": 0.9582504970178928, | |
| "eval_BUILDINGNUMBER_f1": 0.8108632395732298, | |
| "eval_CITY_f1": 0.8010899182561309, | |
| "eval_COMPANYNAME_f1": 0.9436619718309859, | |
| "eval_COUNTY_f1": 0.875219683655536, | |
| "eval_CREDITCARDCVV_f1": 0.8634920634920634, | |
| "eval_CREDITCARDISSUER_f1": 0.9737827715355806, | |
| "eval_CREDITCARDNUMBER_f1": 0.8771266540642721, | |
| "eval_CURRENCYCODE_f1": 0.5565749235474006, | |
| "eval_CURRENCYNAME_f1": 0.2214022140221402, | |
| "eval_CURRENCYSYMBOL_f1": 0.8640308582449373, | |
| "eval_CURRENCY_f1": 0.6542491268917345, | |
| "eval_DATE_f1": 0.8364532019704435, | |
| "eval_DOB_f1": 0.5696361355081556, | |
| "eval_EMAIL_f1": 0.9913686806411837, | |
| "eval_ETHEREUMADDRESS_f1": 0.9903181189488243, | |
| "eval_EYECOLOR_f1": 0.907608695652174, | |
| "eval_FIRSTNAME_f1": 0.8759040730871717, | |
| "eval_GENDER_f1": 0.9323621227887617, | |
| "eval_HEIGHT_f1": 0.9046153846153847, | |
| "eval_IBAN_f1": 0.9899244332493703, | |
| "eval_IPV4_f1": 0.8118195956454121, | |
| "eval_IPV6_f1": 0.8090671316477768, | |
| "eval_IP_f1": 0.11372549019607843, | |
| "eval_JOBAREA_f1": 0.789514263685428, | |
| "eval_JOBTITLE_f1": 0.9805996472663139, | |
| "eval_JOBTYPE_f1": 0.9055649241146712, | |
| "eval_LASTNAME_f1": 0.8178879310344828, | |
| "eval_LITECOINADDRESS_f1": 0.8739002932551319, | |
| "eval_MAC_f1": 1.0, | |
| "eval_MASKEDNUMBER_f1": 0.8319226118500604, | |
| "eval_MIDDLENAME_f1": 0.8419213973799127, | |
| "eval_NEARBYGPSCOORDINATE_f1": 1.0, | |
| "eval_ORDINALDIRECTION_f1": 0.9681528662420382, | |
| "eval_PASSWORD_f1": 0.9595484477892756, | |
| "eval_PHONEIMEI_f1": 0.9930264993026499, | |
| "eval_PHONENUMBER_f1": 0.98068669527897, | |
| "eval_PIN_f1": 0.7867867867867867, | |
| "eval_PREFIX_f1": 0.9354624085163007, | |
| "eval_SECONDARYADDRESS_f1": 0.9967284623773174, | |
| "eval_SEX_f1": 0.9692154915590864, | |
| "eval_SSN_f1": 0.9897959183673469, | |
| "eval_STATE_f1": 0.7407407407407408, | |
| "eval_STREET_f1": 0.7823008849557522, | |
| "eval_TIME_f1": 0.9499575911789652, | |
| "eval_URL_f1": 0.9936406995230525, | |
| "eval_USERAGENT_f1": 0.9976415094339622, | |
| "eval_USERNAME_f1": 0.9331131296449217, | |
| "eval_VEHICLEVIN_f1": 0.9712643678160919, | |
| "eval_VEHICLEVRM_f1": 0.9493333333333334, | |
| "eval_ZIPCODE_f1": 0.8634361233480177, | |
| "eval_loss": 0.10552353411912918, | |
| "eval_overall_accuracy": 0.9609040792185279, | |
| "eval_overall_f1": 0.8814179158519806, | |
| "eval_overall_precision": 0.8683074728018548, | |
| "eval_overall_recall": 0.8949303334436234, | |
| "eval_runtime": 577.0147, | |
| "eval_samples_per_second": 15.078, | |
| "eval_steps_per_second": 0.943, | |
| "total_flos": 7172623426882680.0, | |
| "train_loss": 0.3317324107378379, | |
| "train_runtime": 43559.0225, | |
| "train_samples_per_second": 3.994, | |
| "train_steps_per_second": 0.499 | |
| } |