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hesamheidari/fabert_keyphrase
fabert_keyphrase is a token classification model from hesamheidari. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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.safetensors495 MB · 100%
From the Hugging Face model README
This model is a fine-tuned version of sbunlp/fabert on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1368 | 1.0 | 2107 | 0.1610 | 0.4900 | 0.4727 | 0.4812 | 0.9407 |
| 0.1227 | 2.0 | 4214 | 0.1620 | 0.5066 | 0.4962 | 0.5014 | 0.9415 |
| 0.108 | 3.0 | 6321 | 0.1659 | 0.5072 | 0.5109 | 0.5090 | 0.9407 |
| 0.0943 | 4.0 | 8428 | 0.1749 | 0.4996 | 0.5083 | 0.5039 | 0.9391 |
| 0.0845 | 5.0 | 10535 | 0.1864 | 0.4945 | 0.5211 | 0.5074 | 0.9384 |