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haryoaw/
scenario-TCR-NER_data-univner_half

Name: scenario-TCR-NER_data-univner_half
Availability: InStock

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scenario-TCR-NER_data-univner_half

This model is a fine-tuned version of xlm-roberta-base on the None 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
0.1189	0.58	500	0.0623	0.8010	0.8531	0.8262	0.9822
0.0469	1.17	1000	0.0640	0.8246	0.8567	0.8404	0.9833
0.0348	1.75	1500	0.0668	0.8335	0.8550	0.8441	0.9834
0.0242	2.33	2000	0.0734	0.8202	0.8538	0.8367	0.9826
0.0215	2.91	2500	0.0717	0.8455	0.8598	0.8526	0.9843
0.0142	3.5	3000	0.0802	0.8383	0.8424	0.8404	0.9836
0.0144	4.08	3500	0.0836	0.8443	0.8554	0.8499	0.9843
0.0103	4.66	4000	0.0811	0.8479	0.8590	0.8534	0.9844
0.0087	5.24	4500	0.0887	0.8364	0.8628	0.8494	0.9840
0.0092	5.83	5000	0.0876	0.8367	0.8430	0.8399	0.9833
0.0076	6.41	5500	0.1004	0.8440	0.8495	0.8468	0.9841
0.007	6.99	6000	0.1080	0.8215	0.8518	0.8364	0.9830
0.0055	7.58	6500	0.0988	0.8454	0.8358	0.8406	0.9831
0.0055	8.16	7000	0.0950	0.8485	0.8461	0.8473	0.9839
0.0044	8.74	7500	0.1001	0.8456	0.8414	0.8435	0.9836
0.004	9.32	8000	0.1084	0.8340	0.8495	0.8417	0.9834
0.004	9.91	8500	0.1175	0.8351	0.8505	0.8427	0.9829
0.0033	10.49	9000	0.1160	0.8555	0.8189	0.8368	0.9828