rtm_DistilBERT_5E

This model is a fine-tuned version of distilbert-base-cased on the rotten_tomatoes dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6822	0.09	50	0.6391	0.76
0.5531	0.19	100	0.4684	0.7667
0.4546	0.28	150	0.4479	0.7733
0.4495	0.37	200	0.3953	0.8067
0.4239	0.47	250	0.4211	0.7933
0.3951	0.56	300	0.4126	0.7933
0.3861	0.66	350	0.3950	0.7933
0.4108	0.75	400	0.4091	0.82
0.3778	0.84	450	0.4107	0.7933
0.3627	0.94	500	0.4203	0.7933
0.3648	1.03	550	0.4190	0.8
0.2899	1.12	600	0.4436	0.8
0.2637	1.22	650	0.4504	0.82
0.2885	1.31	700	0.4406	0.82
0.3226	1.4	750	0.4398	0.8333
0.3147	1.5	800	0.4239	0.82
0.2937	1.59	850	0.4227	0.8133
0.3149	1.69	900	0.3791	0.82
0.3227	1.78	950	0.3888	0.8133
0.2727	1.87	1000	0.4215	0.82
0.2722	1.97	1050	0.4099	0.8333
0.1908	2.06	1100	0.4595	0.82
0.2276	2.15	1150	0.4572	0.84
0.2239	2.25	1200	0.4545	0.8333
0.1986	2.34	1250	0.4895	0.82
0.2388	2.43	1300	0.4352	0.86
0.1901	2.53	1350	0.4806	0.84
0.2227	2.62	1400	0.5473	0.8067
0.2221	2.72	1450	0.5010	0.84
0.1955	2.81	1500	0.5315	0.8267
0.2114	2.9	1550	0.5410	0.8133
0.1827	3.0	1600	0.5721	0.8133
0.1527	3.09	1650	0.5616	0.8133
0.1464	3.18	1700	0.5935	0.8067
0.135	3.28	1750	0.6145	0.82
0.1668	3.37	1800	0.6901	0.8067
0.1702	3.46	1850	0.6067	0.8133
0.1738	3.56	1900	0.5981	0.82
0.1506	3.65	1950	0.6073	0.8267
0.1584	3.75	2000	0.6549	0.8133
0.1698	3.84	2050	0.6660	0.8267
0.1626	3.93	2100	0.6645	0.8267
0.1483	4.03	2150	0.6497	0.82
0.1342	4.12	2200	0.6643	0.82
0.1064	4.21	2250	0.6775	0.82
0.1302	4.31	2300	0.6876	0.82
0.1847	4.4	2350	0.6821	0.8133
0.1055	4.49	2400	0.6928	0.8133
0.1372	4.59	2450	0.6877	0.8133
0.131	4.68	2500	0.6769	0.8267
0.1242	4.78	2550	0.6769	0.8267
0.1289	4.87	2600	0.6810	0.82
0.1488	4.96	2650	0.6835	0.82