segformer-b0-finetuned-segments-chargers-2-15

This model is a fine-tuned version of nvidia/mit-b0 on the dskong07/chargers-large-v0.1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5246
• Mean Iou: 0.6936
• Mean Accuracy: 0.7865
• Overall Accuracy: 0.8737
• Accuracy Unlabeled: nan
• Accuracy Screen: 0.8112
• Accuracy Body: 0.8204
• Accuracy Cable: 0.5689
• Accuracy Plug: 0.7794
• Accuracy Void-background: 0.9527
• Iou Unlabeled: nan
• Iou Screen: 0.6428
• Iou Body: 0.7165
• Iou Cable: 0.4784
• Iou Plug: 0.7602
• Iou Void-background: 0.8699

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 6e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Unlabeled	Accuracy Screen	Accuracy Body	Accuracy Cable	Accuracy Plug	Accuracy Void-background	Iou Unlabeled	Iou Screen	Iou Body	Iou Cable	Iou Plug	Iou Void-background
1.5655	0.4545	20	1.5839	0.2857	0.4743	0.6852	nan	0.0011	0.9372	0.2006	0.5724	0.6603	0.0	0.0011	0.5394	0.1392	0.4020	0.6327
1.0387	0.9091	40	1.1224	0.4674	0.5660	0.7519	nan	0.3246	0.9455	0.1082	0.7175	0.7344	nan	0.3106	0.5946	0.0854	0.6450	0.7013
0.8506	1.3636	60	0.9374	0.4166	0.5127	0.7649	nan	0.0088	0.9269	0.0955	0.7074	0.8249	nan	0.0088	0.6031	0.0855	0.6173	0.7685
1.316	1.8182	80	0.8349	0.5009	0.5943	0.7935	nan	0.5485	0.7621	0.1866	0.5533	0.9208	nan	0.4427	0.6167	0.1428	0.5252	0.7769
1.266	2.2727	100	0.7590	0.5428	0.6460	0.7983	nan	0.5567	0.9028	0.2308	0.7277	0.8120	nan	0.4578	0.6421	0.1727	0.6712	0.7704
0.8593	2.7273	120	0.6299	0.5461	0.6352	0.8205	nan	0.5860	0.8529	0.1316	0.7085	0.8969	nan	0.4586	0.6578	0.1155	0.6799	0.8187
0.8198	3.1818	140	0.7950	0.5250	0.6838	0.7766	nan	0.8901	0.6993	0.2443	0.7259	0.8594	nan	0.4157	0.5596	0.1809	0.6593	0.8094
0.5949	3.6364	160	0.5951	0.5629	0.6478	0.8330	nan	0.5695	0.8356	0.1649	0.7372	0.9320	nan	0.4646	0.6751	0.1432	0.6980	0.8337
0.6526	4.0909	180	0.6001	0.5719	0.6773	0.8276	nan	0.6910	0.8250	0.2582	0.7077	0.9048	nan	0.4875	0.6667	0.1978	0.6758	0.8316
0.604	4.5455	200	0.5667	0.5745	0.6851	0.8281	nan	0.6975	0.8459	0.2699	0.7244	0.8878	nan	0.5012	0.6688	0.2147	0.6592	0.8287
0.9183	5.0	220	0.5883	0.5631	0.6876	0.8149	nan	0.8346	0.7327	0.2647	0.6826	0.9237	nan	0.5150	0.6250	0.2047	0.6529	0.8180
0.7613	5.4545	240	0.5747	0.5662	0.6809	0.8123	nan	0.6507	0.8818	0.2722	0.7655	0.8342	nan	0.5111	0.6512	0.2208	0.6570	0.7907
0.5511	5.9091	260	0.5322	0.5933	0.6901	0.8376	nan	0.6194	0.8284	0.3510	0.7269	0.9249	nan	0.4969	0.6815	0.2498	0.6996	0.8388
0.4982	6.3636	280	0.5335	0.5795	0.6651	0.8320	nan	0.5108	0.8423	0.3209	0.7286	0.9230	nan	0.4651	0.6735	0.2494	0.6851	0.8243
0.4108	6.8182	300	0.5281	0.5856	0.7001	0.8354	nan	0.8443	0.7602	0.2416	0.7109	0.9438	nan	0.5248	0.6554	0.2105	0.6875	0.8499
0.3376	7.2727	320	0.5272	0.6009	0.7188	0.8306	nan	0.8168	0.8113	0.3663	0.7066	0.8927	nan	0.5315	0.6551	0.2982	0.6852	0.8345
0.7766	7.7273	340	0.5079	0.6229	0.7564	0.8391	nan	0.8021	0.7792	0.5319	0.7504	0.9184	nan	0.5374	0.6640	0.3668	0.6997	0.8466
0.2429	8.1818	360	0.4761	0.6026	0.6890	0.8481	nan	0.6583	0.8449	0.2794	0.7283	0.9341	nan	0.5177	0.6870	0.2522	0.6996	0.8566
0.3841	8.6364	380	0.5158	0.6200	0.7652	0.8325	nan	0.8574	0.7548	0.5769	0.7249	0.9122	nan	0.5241	0.6429	0.3738	0.7084	0.8507
0.1936	9.0909	400	0.4504	0.6434	0.7384	0.8578	nan	0.7268	0.8556	0.4359	0.7526	0.9212	nan	0.5913	0.7055	0.3452	0.7196	0.8552
0.2613	9.5455	420	0.4961	0.6302	0.7245	0.8470	nan	0.7415	0.7658	0.3729	0.7789	0.9634	nan	0.5875	0.6679	0.3161	0.7391	0.8403
0.4556	10.0	440	0.5313	0.6149	0.7346	0.8324	nan	0.8388	0.7388	0.4024	0.7559	0.9374	nan	0.5525	0.6306	0.3420	0.7108	0.8384
0.3093	10.4545	460	0.5350	0.6375	0.7984	0.8363	nan	0.8549	0.7216	0.6702	0.8157	0.9293	nan	0.5122	0.6350	0.4503	0.7317	0.8582
0.3501	10.9091	480	0.4808	0.6231	0.7178	0.8476	nan	0.7342	0.8303	0.3612	0.7393	0.9242	nan	0.5390	0.6785	0.3196	0.7237	0.8544
0.2578	11.3636	500	0.4619	0.6534	0.7584	0.8571	nan	0.7772	0.7877	0.5154	0.7582	0.9533	nan	0.5924	0.6883	0.4019	0.7278	0.8567
0.2126	11.8182	520	0.4903	0.6421	0.7441	0.8454	nan	0.7623	0.7699	0.5032	0.7381	0.9471	nan	0.5930	0.6614	0.4031	0.7148	0.8381
0.2819	12.2727	540	0.4747	0.6415	0.7479	0.8513	nan	0.7971	0.7860	0.4807	0.7309	0.9447	nan	0.5606	0.6747	0.3977	0.7159	0.8586
0.4983	12.7273	560	0.4771	0.6471	0.7305	0.8557	nan	0.6815	0.8187	0.4402	0.7633	0.9489	nan	0.5985	0.6893	0.3828	0.7182	0.8468
0.2204	13.1818	580	0.5358	0.6215	0.7475	0.8318	nan	0.8870	0.6911	0.4973	0.7026	0.9593	nan	0.5409	0.6175	0.4127	0.6943	0.8421
0.2746	13.6364	600	0.4943	0.6590	0.7715	0.8484	nan	0.7947	0.7570	0.6081	0.7496	0.9482	nan	0.6194	0.6638	0.4429	0.7312	0.8377
0.2906	14.0909	620	0.4353	0.6656	0.7480	0.8677	nan	0.6908	0.8820	0.4950	0.7480	0.9239	nan	0.6107	0.7228	0.4001	0.7317	0.8629
0.2525	14.5455	640	0.4791	0.6443	0.7224	0.8571	nan	0.6094	0.8913	0.4654	0.7341	0.9119	nan	0.5499	0.7035	0.3952	0.7189	0.8540
0.1833	15.0	660	0.4864	0.6493	0.7763	0.8484	nan	0.8969	0.7388	0.5243	0.7716	0.9499	nan	0.5615	0.6540	0.4238	0.7441	0.8632
0.1939	15.4545	680	0.4617	0.6640	0.7551	0.8626	nan	0.7545	0.8548	0.5001	0.7434	0.9229	nan	0.6174	0.7057	0.4156	0.7235	0.8580
0.2707	15.9091	700	0.4290	0.6809	0.7779	0.8708	nan	0.7613	0.8438	0.5709	0.7756	0.9381	nan	0.6280	0.7198	0.4356	0.7521	0.8690
0.3119	16.3636	720	0.5260	0.6407	0.7639	0.8423	nan	0.8560	0.7194	0.5168	0.7685	0.9585	nan	0.5350	0.6394	0.4234	0.7476	0.8579
0.3174	16.8182	740	0.5124	0.6571	0.7863	0.8448	nan	0.8463	0.7425	0.6094	0.7940	0.9396	nan	0.5712	0.6501	0.4540	0.7623	0.8480
0.2184	17.2727	760	0.4456	0.6717	0.7646	0.8642	nan	0.8054	0.8222	0.4617	0.7932	0.9402	nan	0.6414	0.7052	0.3969	0.7615	0.8538
0.1249	17.7273	780	0.4879	0.6582	0.7493	0.8532	nan	0.7889	0.7806	0.4841	0.7405	0.9525	nan	0.6257	0.6726	0.4193	0.7299	0.8434
0.1712	18.1818	800	0.5040	0.6731	0.7851	0.8483	nan	0.8385	0.7146	0.5750	0.8302	0.9672	nan	0.6569	0.6503	0.4501	0.7794	0.8289
0.2217	18.6364	820	0.5103	0.6633	0.7491	0.8509	nan	0.7282	0.7919	0.5329	0.7477	0.9450	nan	0.6338	0.6720	0.4389	0.7388	0.8331
0.3263	19.0909	840	0.5004	0.6648	0.7623	0.8554	nan	0.8285	0.7740	0.4984	0.7578	0.9530	nan	0.6267	0.6735	0.4297	0.7451	0.8489
0.1662	19.5455	860	0.4651	0.6780	0.7726	0.8644	nan	0.8039	0.8349	0.5213	0.7743	0.9287	nan	0.6384	0.7013	0.4381	0.7540	0.8582
0.1361	20.0	880	0.4748	0.6767	0.7656	0.8678	nan	0.7775	0.8272	0.5149	0.7618	0.9467	nan	0.6257	0.7085	0.4340	0.7511	0.8644
0.2124	20.4545	900	0.4660	0.6767	0.7776	0.8666	nan	0.8329	0.8000	0.5421	0.7603	0.9528	nan	0.6190	0.7016	0.4474	0.7487	0.8671
0.2573	20.9091	920	0.4938	0.6776	0.7773	0.8651	nan	0.8314	0.8083	0.5014	0.8013	0.9440	nan	0.6328	0.6987	0.4245	0.7700	0.8617
0.1497	21.3636	940	0.4430	0.6854	0.7821	0.8745	nan	0.7735	0.8398	0.5606	0.7905	0.9461	nan	0.6077	0.7236	0.4501	0.7661	0.8793
0.1861	21.8182	960	0.5097	0.6506	0.7678	0.8542	nan	0.8649	0.7894	0.5257	0.7242	0.9346	nan	0.5470	0.6768	0.4381	0.7176	0.8735
0.1572	22.2727	980	0.4777	0.6711	0.7551	0.8675	nan	0.7502	0.8347	0.4718	0.7713	0.9476	nan	0.6129	0.7084	0.4165	0.7517	0.8658
0.1082	22.7273	1000	0.4540	0.6867	0.7899	0.8677	nan	0.7930	0.8204	0.6061	0.7906	0.9395	nan	0.6199	0.7075	0.4731	0.7686	0.8645
0.1285	23.1818	1020	0.4463	0.6797	0.7735	0.8694	nan	0.7947	0.8460	0.5223	0.7717	0.9326	nan	0.6129	0.7137	0.4458	0.7557	0.8703
0.1978	23.6364	1040	0.4781	0.6904	0.7899	0.8704	nan	0.8070	0.7945	0.5618	0.8244	0.9619	nan	0.6368	0.7081	0.4667	0.7763	0.8642
0.1879	24.0909	1060	0.4848	0.6803	0.7783	0.8687	nan	0.8016	0.8162	0.5624	0.7626	0.9489	nan	0.6187	0.7084	0.4558	0.7497	0.8689
0.102	24.5455	1080	0.4841	0.6775	0.7682	0.8680	nan	0.7574	0.8436	0.5251	0.7786	0.9365	nan	0.6052	0.7108	0.4453	0.7586	0.8675
0.2149	25.0	1100	0.4672	0.6908	0.7884	0.8737	nan	0.8144	0.8204	0.5707	0.7849	0.9515	nan	0.6215	0.7174	0.4772	0.7633	0.8747
1.1322	25.4545	1120	0.4990	0.6663	0.7486	0.8681	nan	0.7371	0.8434	0.4733	0.7423	0.9470	nan	0.5989	0.7132	0.4169	0.7335	0.8689
0.0783	25.9091	1140	0.4601	0.6975	0.8088	0.8743	nan	0.8220	0.8114	0.6712	0.7896	0.9496	nan	0.6191	0.7188	0.5039	0.7694	0.8760
0.1457	26.3636	1160	0.4470	0.6896	0.7797	0.8757	nan	0.7891	0.8530	0.5372	0.7795	0.9395	nan	0.6254	0.7267	0.4578	0.7617	0.8764
0.1361	26.8182	1180	0.5201	0.6678	0.7768	0.8604	nan	0.8519	0.7749	0.5550	0.7467	0.9552	nan	0.5847	0.6838	0.4638	0.7387	0.8679
0.1691	27.2727	1200	0.4951	0.6754	0.7539	0.8697	nan	0.7242	0.8636	0.4831	0.7634	0.9356	nan	0.6207	0.7152	0.4287	0.7453	0.8672
0.1999	27.7273	1220	0.4614	0.6979	0.8111	0.8711	nan	0.8696	0.7905	0.6040	0.8397	0.9518	nan	0.6315	0.7069	0.4962	0.7861	0.8686
0.0889	28.1818	1240	0.4832	0.6938	0.7830	0.8728	nan	0.8059	0.8247	0.5632	0.7714	0.9496	nan	0.6636	0.7167	0.4688	0.7563	0.8635
0.1142	28.6364	1260	0.4679	0.6879	0.7740	0.8739	nan	0.7970	0.8397	0.5295	0.7576	0.9464	nan	0.6528	0.7206	0.4518	0.7450	0.8692
0.0918	29.0909	1280	0.5233	0.6846	0.7799	0.8648	nan	0.7956	0.7887	0.5848	0.7716	0.9589	nan	0.6379	0.6956	0.4797	0.7548	0.8551
0.1316	29.5455	1300	0.5407	0.6767	0.7714	0.8627	nan	0.8172	0.7958	0.5277	0.7653	0.9511	nan	0.6302	0.6903	0.4545	0.7513	0.8573
0.1038	30.0	1320	0.5312	0.6896	0.7940	0.8614	nan	0.8361	0.7694	0.6171	0.7919	0.9552	nan	0.6347	0.6822	0.5066	0.7728	0.8519
0.0852	30.4545	1340	0.5382	0.6821	0.7743	0.8662	nan	0.8174	0.8112	0.5254	0.7705	0.9471	nan	0.6370	0.6993	0.4586	0.7549	0.8608
0.1675	30.9091	1360	0.5164	0.6961	0.7941	0.8706	nan	0.7941	0.8111	0.6478	0.7668	0.9505	nan	0.6395	0.7098	0.5145	0.7536	0.8630
0.1527	31.3636	1380	0.4914	0.6975	0.7940	0.8734	nan	0.8204	0.8185	0.5917	0.7903	0.9492	nan	0.6434	0.7152	0.4932	0.7670	0.8686
0.1452	31.8182	1400	0.4774	0.6926	0.7818	0.8759	nan	0.7997	0.8295	0.5545	0.7711	0.9541	nan	0.6384	0.7226	0.4719	0.7560	0.8740
0.118	32.2727	1420	0.5084	0.6836	0.7877	0.8683	nan	0.8095	0.8179	0.5938	0.7752	0.9421	nan	0.6059	0.7065	0.4776	0.7570	0.8712
0.084	32.7273	1440	0.5185	0.6837	0.7724	0.8705	nan	0.7650	0.8410	0.5464	0.7686	0.9413	nan	0.6181	0.7139	0.4632	0.7545	0.8688
0.0946	33.1818	1460	0.5205	0.6840	0.7788	0.8700	nan	0.8178	0.8142	0.5450	0.7654	0.9516	nan	0.6270	0.7076	0.4633	0.7523	0.8701
0.1055	33.6364	1480	0.4754	0.6966	0.7909	0.8787	nan	0.8024	0.8560	0.5764	0.7817	0.9381	nan	0.6386	0.7327	0.4761	0.7567	0.8791
0.0648	34.0909	1500	0.4594	0.7028	0.8001	0.8794	nan	0.8077	0.8491	0.6292	0.7747	0.9400	nan	0.6393	0.7337	0.5006	0.7623	0.8784
0.105	34.5455	1520	0.4706	0.6978	0.8011	0.8757	nan	0.8362	0.8296	0.6192	0.7779	0.9424	nan	0.6291	0.7220	0.4987	0.7616	0.8775
1.4787	35.0	1540	0.4627	0.7087	0.7987	0.8810	nan	0.7919	0.8393	0.6184	0.7920	0.9521	nan	0.6504	0.7338	0.5105	0.7724	0.8763
0.1147	35.4545	1560	0.4701	0.7046	0.8014	0.8762	nan	0.7854	0.8391	0.6550	0.7862	0.9412	nan	0.6453	0.7250	0.5151	0.7680	0.8699
0.195	35.9091	1580	0.4830	0.6947	0.7915	0.8748	nan	0.8244	0.8209	0.5901	0.7709	0.9514	nan	0.6360	0.7180	0.4902	0.7551	0.8743
0.3486	36.3636	1600	0.4924	0.6965	0.7919	0.8764	nan	0.8062	0.8362	0.5987	0.7725	0.9459	nan	0.6405	0.7245	0.4880	0.7541	0.8752
0.1099	36.8182	1620	0.4828	0.6952	0.7860	0.8761	nan	0.7993	0.8391	0.5788	0.7665	0.9462	nan	0.6440	0.7243	0.4825	0.7524	0.8730
0.0522	37.2727	1640	0.4881	0.6936	0.7887	0.8723	nan	0.8043	0.8286	0.5928	0.7742	0.9436	nan	0.6372	0.7160	0.4903	0.7572	0.8674
0.1351	37.7273	1660	0.4858	0.6964	0.7871	0.8757	nan	0.8118	0.8421	0.5696	0.7700	0.9418	nan	0.6471	0.7234	0.4857	0.7540	0.8718
0.203	38.1818	1680	0.5016	0.6945	0.7850	0.8725	nan	0.8046	0.8431	0.5647	0.7771	0.9356	nan	0.6460	0.7160	0.4839	0.7596	0.8671
0.0954	38.6364	1700	0.4769	0.7112	0.8060	0.8779	nan	0.8099	0.8198	0.6541	0.7918	0.9541	nan	0.6605	0.7232	0.5307	0.7715	0.8699
0.0995	39.0909	1720	0.4993	0.6996	0.7862	0.8747	nan	0.7803	0.8414	0.5899	0.7760	0.9431	nan	0.6558	0.7209	0.4950	0.7601	0.8661
0.1813	39.5455	1740	0.4946	0.6987	0.7918	0.8757	nan	0.8139	0.8281	0.5865	0.7809	0.9493	nan	0.6520	0.7207	0.4905	0.7589	0.8713
0.0621	40.0	1760	0.4762	0.7033	0.7927	0.8803	nan	0.8028	0.8447	0.5892	0.7781	0.9485	nan	0.6568	0.7321	0.4905	0.7598	0.8774
0.0687	40.4545	1780	0.4884	0.7011	0.7915	0.8787	nan	0.7979	0.8304	0.6021	0.7714	0.9559	nan	0.6511	0.7281	0.4949	0.7560	0.8752
0.1386	40.9091	1800	0.4828	0.6969	0.7889	0.8782	nan	0.7934	0.8515	0.5913	0.7668	0.9417	nan	0.6379	0.7306	0.4859	0.7523	0.8778
0.0459	41.3636	1820	0.4872	0.6968	0.7956	0.8762	nan	0.8166	0.8278	0.6053	0.7798	0.9488	nan	0.6313	0.7230	0.4910	0.7618	0.8769
0.0411	41.8182	1840	0.4718	0.7066	0.7973	0.8807	nan	0.7948	0.8468	0.6196	0.7786	0.9467	nan	0.6525	0.7339	0.5061	0.7630	0.8772
0.0401	42.2727	1860	0.4735	0.7065	0.7990	0.8800	nan	0.8039	0.8356	0.6113	0.7926	0.9513	nan	0.6451	0.7300	0.5087	0.7711	0.8777
1.8317	42.7273	1880	0.4900	0.6958	0.7804	0.8790	nan	0.7847	0.8469	0.5523	0.7673	0.9509	nan	0.6388	0.7309	0.4760	0.7554	0.8779
0.1147	43.1818	1900	0.4926	0.6940	0.7874	0.8764	nan	0.8138	0.8472	0.5618	0.7744	0.9396	nan	0.6277	0.7249	0.4798	0.7588	0.8787
0.0765	43.6364	1920	0.4913	0.6995	0.7907	0.8788	nan	0.7868	0.8574	0.5862	0.7845	0.9387	nan	0.6380	0.7324	0.4888	0.7614	0.8772
0.1342	44.0909	1940	0.4832	0.6969	0.7836	0.8793	nan	0.7621	0.8697	0.5768	0.7730	0.9365	nan	0.6321	0.7356	0.4813	0.7571	0.8786
0.0698	44.5455	1960	0.4760	0.7022	0.7965	0.8799	nan	0.8003	0.8392	0.6173	0.7756	0.9500	nan	0.6399	0.7314	0.4997	0.7599	0.8801
0.0881	45.0	1980	0.4828	0.7027	0.7946	0.8807	nan	0.8076	0.8461	0.5947	0.7775	0.9472	nan	0.6397	0.7330	0.4984	0.7609	0.8816
0.0903	45.4545	2000	0.4890	0.7004	0.7894	0.8796	nan	0.8024	0.8472	0.5696	0.7810	0.9468	nan	0.6392	0.7313	0.4905	0.7620	0.8792
0.1647	45.9091	2020	0.4961	0.7043	0.8010	0.8782	nan	0.8182	0.8313	0.6124	0.7948	0.9483	nan	0.6389	0.7256	0.5088	0.7711	0.8772
0.0829	46.3636	2040	0.4977	0.7014	0.7929	0.8785	nan	0.8011	0.8502	0.5970	0.7755	0.9409	nan	0.6419	0.7295	0.4988	0.7598	0.8769
0.1189	46.8182	2060	0.4946	0.7029	0.7989	0.8773	nan	0.8201	0.8269	0.5936	0.8040	0.9500	nan	0.6383	0.7231	0.5006	0.7769	0.8757
0.0862	47.2727	2080	0.5052	0.7012	0.8009	0.8752	nan	0.8232	0.8213	0.6186	0.7936	0.9481	nan	0.6410	0.7184	0.5038	0.7703	0.8726
0.0754	47.7273	2100	0.5120	0.6969	0.7851	0.8758	nan	0.7846	0.8404	0.5816	0.7725	0.9464	nan	0.6457	0.7239	0.4867	0.7575	0.8708
0.1364	48.1818	2120	0.5077	0.6958	0.7822	0.8769	nan	0.7784	0.8646	0.5686	0.7654	0.9341	nan	0.6430	0.7293	0.4803	0.7529	0.8737
0.1038	48.6364	2140	0.5018	0.6965	0.7898	0.8760	nan	0.8126	0.8410	0.5757	0.7779	0.9419	nan	0.6405	0.7232	0.4853	0.7590	0.8745
0.1046	49.0909	2160	0.4999	0.6968	0.7912	0.8755	nan	0.8105	0.8361	0.5884	0.7772	0.9439	nan	0.6402	0.7216	0.4901	0.7588	0.8736
0.0701	49.5455	2180	0.5165	0.6942	0.7917	0.8743	nan	0.8236	0.8410	0.5828	0.7745	0.9367	nan	0.6330	0.7200	0.4862	0.7573	0.8746
0.5858	50.0	2200	0.5246	0.6936	0.7865	0.8737	nan	0.8112	0.8204	0.5689	0.7794	0.9527	nan	0.6428	0.7165	0.4784	0.7602	0.8699

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cpu
• Datasets 3.2.0
• Tokenizers 0.21.0