Training Loss	Epoch	Step	Validation Loss	Precision Macro	Recall Macro	F1 Macro	F1 Neutral	F1 Toxic
0.6127	0.23	100	0.4477	0.8252	0.825	0.8250	0.8274	0.8226
0.3728	0.46	200	0.2852	0.8877	0.8875	0.8875	0.8886	0.8864
0.2888	0.69	300	0.2405	0.9039	0.9038	0.9037	0.9047	0.9028
0.2724	0.92	400	0.2288	0.9110	0.9094	0.9093	0.9122	0.9064
0.2387	1.15	500	0.2161	0.9132	0.9125	0.9125	0.9143	0.9106
0.2189	1.38	600	0.2098	0.9206	0.9206	0.9206	0.9208	0.9205
0.1783	1.61	700	0.2045	0.9233	0.9231	0.9231	0.9238	0.9224
0.1911	1.84	800	0.2098	0.9184	0.9175	0.9175	0.9155	0.9194
0.1749	2.07	900	0.1947	0.9271	0.9269	0.9269	0.9277	0.9260
0.1728	2.3	1000	0.1893	0.9263	0.9263	0.9262	0.9265	0.9260
0.1628	2.53	1100	0.1926	0.9276	0.9275	0.9275	0.9270	0.9280
0.1545	2.76	1200	0.1889	0.9299	0.9294	0.9294	0.9306	0.9281
0.1659	2.99	1300	0.1893	0.9263	0.9263	0.9263	0.9263	0.9263
0.1433	3.22	1400	0.1952	0.9264	0.9263	0.9262	0.9256	0.9269
0.1243	3.45	1500	0.1838	0.9300	0.93	0.9300	0.9303	0.9296
0.1357	3.68	1600	0.1846	0.9370	0.9356	0.9356	0.9374	0.9338
0.1419	3.91	1700	0.1793	0.9339	0.9331	0.9331	0.9345	0.9317
0.1205	4.14	1800	0.1896	0.9306	0.9306	0.9306	0.9306	0.9307
0.1159	4.37	1900	0.1905	0.9354	0.935	0.9350	0.9360	0.9340
0.1185	4.6	2000	0.1893	0.9400	0.9387	0.9387	0.9403	0.9371
0.102	4.83	2100	0.1944	0.9415	0.9406	0.9406	0.9419	0.9393
0.1222	5.06	2200	0.1880	0.9390	0.9387	0.9387	0.9394	0.9381
0.1006	5.29	2300	0.1964	0.9331	0.9331	0.9331	0.9330	0.9333
0.108	5.52	2400	0.1901	0.9382	0.9381	0.9381	0.9384	0.9379
0.1059	5.75	2500	0.1907	0.9401	0.94	0.9400	0.9404	0.9396
0.1033	5.98	2600	0.1905	0.9409	0.94	0.9400	0.9413	0.9386
0.0969	6.21	2700	0.1969	0.9345	0.9344	0.9344	0.9338	0.9349
0.0826	6.44	2800	0.1952	0.9407	0.9406	0.9406	0.9410	0.9402
0.1055	6.67	2900	0.1967	0.9375	0.9375	0.9375	0.9373	0.9377
0.0982	6.9	3000	0.2063	0.9394	0.9381	0.9381	0.9397	0.9364
0.0862	7.13	3100	0.2056	0.9414	0.9412	0.9412	0.9418	0.9407
0.0811	7.36	3200	0.2054	0.9414	0.9412	0.9412	0.9418	0.9407
0.0908	7.59	3300	0.2078	0.9394	0.9394	0.9394	0.9396	0.9392
0.092	7.82	3400	0.2003	0.9400	0.94	0.9400	0.9401	0.9399
0.0834	8.05	3500	0.2039	0.9394	0.9394	0.9394	0.9392	0.9396
0.0747	8.28	3600	0.2018	0.9413	0.9413	0.9412	0.9415	0.9410
0.0898	8.51	3700	0.2009	0.94	0.94	0.94	0.94	0.94
0.077	8.74	3800	0.2022	0.9410	0.9406	0.9406	0.9415	0.9398
0.087	8.97	3900	0.2055	0.9382	0.9381	0.9381	0.9385	0.9377
0.0647	9.2	4000	0.2062	0.9401	0.94	0.9400	0.9405	0.9395
0.0736	9.43	4100	0.2081	0.9389	0.9387	0.9387	0.9393	0.9382
0.08	9.66	4200	0.2087	0.9395	0.9394	0.9394	0.9399	0.9388
0.083	9.89	4300	0.2087	0.9395	0.9394	0.9394	0.9398	0.9390

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3

BunnyNoBugs/rubert-tiny2-russe-toxicity

rubert-tiny2-russe-toxicity

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

BunnyNoBugs/
rubert-tiny2-russe-toxicity