README.md

---
license: mit
datasets:
- DFKI-SLT/tacred
language:
- en
metrics:
- f1
library_name: transformers
pipeline_tag: text-classification

# Optional. Add this if you want to encode your eval results in a structured way.
model-index:
- name: re_bert-base_tacred
  results:
  - task:
      type: relation-classification             # Required. Example: automatic-speech-recognition
      name: Relation Classification             # Optional. Example: Speech Recognition
    dataset:
      type: DFKI-SLT/tacred           # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
      name: TAC Relation Extraction Dataset          # Required. A pretty name for the dataset. Example: Common Voice (French)
      config: revisited      # Optional. The name of the dataset configuration used in `load_dataset()`. Example: fr in `load_dataset("common_voice", "fr")`. See the `datasets` docs for more info: https://huggingface.co/docs/datasets/package_reference/loading_methods#datasets.load_dataset.name
      split: test        # Optional. Example: test
    metrics:
      - type: f1         # Required. Example: wer. Use metric id from https://hf.co/metrics
        value: 0.7985       # Required. Example: 20.90
        name: test/f1         # Optional. Example: Test WER
        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
---