
[allenai/tk-instruct-base-def-pos](https://huggingface.co/allenai/tk-instruct-base-def-pos) model fined tuned on custom KeyBert default keywords extracter model - [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) and ABSA model - [yangheng/deberta-v3-base-absa-v1.1](https://huggingface.co/yangheng/deberta-v3-base-absa-v1.1) auto annotated hospital reviews [keywords,polarity] dataset.


Training Results:

Epoch | Training Loss | Validation Loss

1 | 0.150800 | 0.112104

2 | 0.103700 | 0.074400

3 | 0.074500 | 0.065034

4 | 0.065900 | 0.062676

5 | 0.059700 | 0.058017

6 | 0.050700 | 0.056635

7 | 0.046500 | 0.056589

8 | 0.046300 | 0.056924


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Evaluation Results:

Train Precision:  0.9552227554840818

Train Recall:  0.9552107544443746

Train F1:  0.9552167549265339

Test Precision:  0.9300919842312746

Test Recall:  0.9301530981010578

Test F1:  0.9301225401622918

UnseenTest Precision:  0.9329632792485055

UnseenTest Recall:  0.9329632792485055

UnseenTest F1:  0.9329632792485054
{"license": "cc-by-nc-4.0"}
transformers pytorch t5 text2text-generation license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible text-generation-inference region:us