modernbert-medium-amharic-32k

This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.2505
Model Preparation Time: 0.0018

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: 0.0001
train_batch_size: 160
eval_batch_size: 160
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
lr_scheduler_warmup_ratio: 0.1
lr_scheduler_warmup_steps: 10000
num_epochs: 32
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time
9.7902	0.1249	840	8.9451	0.0018
8.4279	0.2498	1680	8.1059	0.0018
7.8804	0.3747	2520	7.6286	0.0018
7.2817	0.4996	3360	6.9665	0.0018
6.7251	0.6244	4200	6.5003	0.0018
6.3085	0.7493	5040	6.1143	0.0018
5.9401	0.8742	5880	5.7576	0.0018
5.5838	0.9991	6720	5.4081	0.0018
5.2326	1.1240	7560	5.0634	0.0018
4.9028	1.2489	8400	4.7484	0.0018
4.6081	1.3738	9240	4.4710	0.0018
4.3543	1.4987	10080	4.2316	0.0018
4.1333	1.6236	10920	4.0414	0.0018
3.9614	1.7484	11760	3.8866	0.0018
3.8307	1.8733	12600	3.7526	0.0018
3.7194	1.9982	13440	3.6655	0.0018
3.6201	2.1231	14280	3.5835	0.0018
3.55	2.2480	15120	3.5199	0.0018
3.486	2.3729	15960	3.4576	0.0018
3.4329	2.4978	16800	3.4101	0.0018
3.3823	2.6227	17640	3.3603	0.0018
3.3336	2.7475	18480	3.3151	0.0018
3.3001	2.8724	19320	3.2799	0.0018
3.2564	2.9973	20160	3.2413	0.0018
3.2167	3.1222	21000	3.2086	0.0018
3.185	3.2471	21840	3.1729	0.0018
3.1562	3.3720	22680	3.1419	0.0018
3.1297	3.4969	23520	3.1340	0.0018
3.1039	3.6218	24360	3.0988	0.0018
3.084	3.7467	25200	3.0719	0.0018
3.0624	3.8715	26040	3.0589	0.0018
3.0377	3.9964	26880	3.0316	0.0018
3.0094	4.1213	27720	3.0182	0.0018
2.9898	4.2462	28560	3.0015	0.0018
2.9737	4.3711	29400	2.9769	0.0018
2.9583	4.4960	30240	2.9632	0.0018
2.9433	4.6209	31080	2.9401	0.0018
2.9282	4.7458	31920	2.9166	0.0018
2.9148	4.8707	32760	2.9144	0.0018
2.9028	4.9955	33600	2.8962	0.0018
2.8735	5.1204	34440	2.8910	0.0018
2.8645	5.2453	35280	2.8809	0.0018
2.8557	5.3702	36120	2.8674	0.0018
2.8409	5.4951	36960	2.8418	0.0018
2.8309	5.6200	37800	2.8343	0.0018
2.8194	5.7449	38640	2.8334	0.0018
2.8121	5.8698	39480	2.8114	0.0018
2.8005	5.9946	40320	2.8057	0.0018
2.7761	6.1195	41160	2.8075	0.0018
2.7691	6.2444	42000	2.7829	0.0018
2.7644	6.3693	42840	2.7794	0.0018
2.7557	6.4942	43680	2.7668	0.0018
2.748	6.6191	44520	2.7544	0.0018
2.7354	6.7440	45360	2.7461	0.0018
2.7317	6.8689	46200	2.7419	0.0018
2.7242	6.9938	47040	2.7316	0.0018
2.7032	7.1186	47880	2.7293	0.0018
2.6991	7.2435	48720	2.7157	0.0018
2.6917	7.3684	49560	2.7101	0.0018
2.689	7.4933	50400	2.7082	0.0018
2.6805	7.6182	51240	2.6988	0.0018
2.6742	7.7431	52080	2.6902	0.0018
2.6714	7.8680	52920	2.6819	0.0018
2.6668	7.9929	53760	2.6772	0.0018
2.6425	8.1178	54600	2.6705	0.0018
2.6387	8.2426	55440	2.6682	0.0018
2.6351	8.3675	56280	2.6562	0.0018
2.6343	8.4924	57120	2.6499	0.0018
2.6286	8.6173	57960	2.6480	0.0018
2.6237	8.7422	58800	2.6473	0.0018
2.6221	8.8671	59640	2.6284	0.0018
2.6134	8.9920	60480	2.6271	0.0018
2.5943	9.1169	61320	2.6303	0.0018
2.5975	9.2417	62160	2.6180	0.0018
2.5897	9.3666	63000	2.6117	0.0018
2.5867	9.4915	63840	2.6102	0.0018
2.582	9.6164	64680	2.5970	0.0018
2.5795	9.7413	65520	2.6003	0.0018
2.5748	9.8662	66360	2.5937	0.0018
2.5684	9.9911	67200	2.5877	0.0018
2.553	10.1160	68040	2.5921	0.0018
2.555	10.2409	68880	2.5877	0.0018
2.5497	10.3657	69720	2.5732	0.0018
2.5525	10.4906	70560	2.5714	0.0018
2.5429	10.6155	71400	2.5703	0.0018
2.5421	10.7404	72240	2.5672	0.0018
2.5398	10.8653	73080	2.5627	0.0018
2.5323	10.9902	73920	2.5595	0.0018
2.518	11.1151	74760	2.5462	0.0018
2.515	11.2400	75600	2.5546	0.0018
2.5152	11.3649	76440	2.5428	0.0018
2.512	11.4897	77280	2.5347	0.0018
2.5132	11.6146	78120	2.5453	0.0018
2.5056	11.7395	78960	2.5306	0.0018
2.5035	11.8644	79800	2.5265	0.0018
2.5044	11.9893	80640	2.5222	0.0018
2.4849	12.1142	81480	2.5327	0.0018
2.4875	12.2391	82320	2.5261	0.0018
2.4859	12.3640	83160	2.5190	0.0018
2.4828	12.4888	84000	2.5112	0.0018
2.479	12.6137	84840	2.5071	0.0018
2.4762	12.7386	85680	2.5027	0.0018
2.4768	12.8635	86520	2.5072	0.0018
2.472	12.9884	87360	2.4876	0.0018
2.4571	13.1133	88200	2.4961	0.0018
2.4578	13.2382	89040	2.4876	0.0018
2.4518	13.3631	89880	2.4921	0.0018
2.4574	13.4880	90720	2.4857	0.0018
2.4548	13.6128	91560	2.4841	0.0018
2.4492	13.7377	92400	2.4803	0.0018
2.4489	13.8626	93240	2.4827	0.0018
2.4459	13.9875	94080	2.4761	0.0018
2.4345	14.1124	94920	2.4744	0.0018
2.4317	14.2373	95760	2.4719	0.0018
2.43	14.3622	96600	2.4650	0.0018
2.4342	14.4871	97440	2.4541	0.0018
2.4305	14.6120	98280	2.4639	0.0018
2.4248	14.7368	99120	2.4631	0.0018
2.426	14.8617	99960	2.4515	0.0018
2.4245	14.9866	100800	2.4575	0.0018
2.4114	15.1115	101640	2.4604	0.0018
2.4071	15.2364	102480	2.4520	0.0018
2.4083	15.3613	103320	2.4480	0.0018
2.4041	15.4862	104160	2.4421	0.0018
2.4057	15.6111	105000	2.4427	0.0018
2.4069	15.7360	105840	2.4477	0.0018
2.4051	15.8608	106680	2.4403	0.0018
2.4021	15.9857	107520	2.4481	0.0018
2.3886	16.1106	108360	2.4382	0.0018
2.3876	16.2355	109200	2.4311	0.0018
2.3891	16.3604	110040	2.4271	0.0018
2.3853	16.4853	110880	2.4290	0.0018
2.388	16.6102	111720	2.4284	0.0018
2.3861	16.7351	112560	2.4282	0.0018
2.3847	16.8599	113400	2.4206	0.0018
2.3828	16.9848	114240	2.4247	0.0018
2.371	17.1097	115080	2.4128	0.0018
2.3695	17.2346	115920	2.4041	0.0018
2.3693	17.3595	116760	2.4086	0.0018
2.3669	17.4844	117600	2.4096	0.0018
2.3672	17.6093	118440	2.4118	0.0018
2.3689	17.7342	119280	2.4080	0.0018
2.3625	17.8591	120120	2.3945	0.0018
2.3618	17.9839	120960	2.4039	0.0018
2.3518	18.1088	121800	2.3983	0.0018
2.3551	18.2337	122640	2.3955	0.0018
2.3492	18.3586	123480	2.3946	0.0018
2.3491	18.4835	124320	2.3924	0.0018
2.3505	18.6084	125160	2.3953	0.0018
2.3503	18.7333	126000	2.3955	0.0018
2.3478	18.8582	126840	2.3878	0.0018
2.3474	18.9831	127680	2.3870	0.0018
2.3339	19.1079	128520	2.3850	0.0018
2.3385	19.2328	129360	2.3855	0.0018
2.3341	19.3577	130200	2.3786	0.0018
2.3381	19.4826	131040	2.3737	0.0018
2.3298	19.6075	131880	2.3733	0.0018
2.3336	19.7324	132720	2.3724	0.0018
2.3315	19.8573	133560	2.3711	0.0018
2.3324	19.9822	134400	2.3644	0.0018
2.3183	20.1070	135240	2.3774	0.0018
2.3195	20.2319	136080	2.3710	0.0018
2.3199	20.3568	136920	2.3710	0.0018
2.319	20.4817	137760	2.3574	0.0018
2.3202	20.6066	138600	2.3547	0.0018
2.3164	20.7315	139440	2.3651	0.0018
2.3164	20.8564	140280	2.3638	0.0018
2.3169	20.9813	141120	2.3609	0.0018
2.3048	21.1062	141960	2.3642	0.0018
2.3035	21.2310	142800	2.3641	0.0018
2.3061	21.3559	143640	2.3534	0.0018
2.3043	21.4808	144480	2.3568	0.0018
2.3043	21.6057	145320	2.3583	0.0018
2.3047	21.7306	146160	2.3521	0.0018
2.3032	21.8555	147000	2.3546	0.0018
2.3016	21.9804	147840	2.3519	0.0018
2.2917	22.1053	148680	2.3346	0.0018
2.2935	22.2302	149520	2.3432	0.0018
2.2912	22.3550	150360	2.3410	0.0018
2.2929	22.4799	151200	2.3394	0.0018
2.2905	22.6048	152040	2.3385	0.0018
2.2914	22.7297	152880	2.3315	0.0018
2.2905	22.8546	153720	2.3341	0.0018
2.2925	22.9795	154560	2.3362	0.0018
2.2798	23.1044	155400	2.3437	0.0018
2.28	23.2293	156240	2.3295	0.0018
2.2761	23.3541	157080	2.3256	0.0018
2.2776	23.4790	157920	2.3312	0.0018
2.2767	23.6039	158760	2.3289	0.0018
2.2774	23.7288	159600	2.3284	0.0018
2.2787	23.8537	160440	2.3250	0.0018
2.2739	23.9786	161280	2.3261	0.0018
2.267	24.1035	162120	2.3241	0.0018
2.2661	24.2284	162960	2.3222	0.0018
2.2644	24.3533	163800	2.3291	0.0018
2.2647	24.4781	164640	2.3198	0.0018
2.263	24.6030	165480	2.3186	0.0018
2.2671	24.7279	166320	2.3198	0.0018
2.2662	24.8528	167160	2.3177	0.0018
2.2641	24.9777	168000	2.3102	0.0018
2.2553	25.1026	168840	2.3185	0.0018
2.2547	25.2275	169680	2.3063	0.0018
2.2558	25.3524	170520	2.3042	0.0018
2.2556	25.4773	171360	2.3110	0.0018
2.2529	25.6021	172200	2.3106	0.0018
2.2535	25.7270	173040	2.3057	0.0018
2.2547	25.8519	173880	2.3117	0.0018
2.2546	25.9768	174720	2.3055	0.0018
2.2465	26.1017	175560	2.3035	0.0018
2.2415	26.2266	176400	2.3056	0.0018
2.2497	26.3515	177240	2.2983	0.0018
2.2422	26.4764	178080	2.2987	0.0018
2.2423	26.6012	178920	2.2987	0.0018
2.2407	26.7261	179760	2.2946	0.0018
2.2412	26.8510	180600	2.2873	0.0018
2.2426	26.9759	181440	2.2966	0.0018
2.2345	27.1008	182280	2.2956	0.0018
2.2359	27.2257	183120	2.2895	0.0018
2.2361	27.3506	183960	2.2884	0.0018
2.2361	27.4755	184800	2.2931	0.0018
2.2335	27.6004	185640	2.2840	0.0018
2.2318	27.7252	186480	2.2819	0.0018
2.2297	27.8501	187320	2.2834	0.0018
2.2283	27.9750	188160	2.2902	0.0018
2.2253	28.0999	189000	2.2932	0.0018
2.224	28.2248	189840	2.2878	0.0018
2.2252	28.3497	190680	2.2812	0.0018
2.2222	28.4746	191520	2.2802	0.0018
2.221	28.5995	192360	2.2781	0.0018
2.224	28.7244	193200	2.2783	0.0018
2.2206	28.8492	194040	2.2776	0.0018
2.224	28.9741	194880	2.2716	0.0018
2.2137	29.0990	195720	2.2868	0.0018
2.2178	29.2239	196560	2.2783	0.0018
2.2163	29.3488	197400	2.2689	0.0018
2.2143	29.4737	198240	2.2677	0.0018
2.2139	29.5986	199080	2.2765	0.0018
2.2134	29.7235	199920	2.2711	0.0018
2.2138	29.8483	200760	2.2725	0.0018
2.2148	29.9732	201600	2.2738	0.0018
2.2126	30.0981	202440	2.2757	0.0018
2.2093	30.2230	203280	2.2714	0.0018
2.2076	30.3479	204120	2.2771	0.0018
2.2092	30.4728	204960	2.2673	0.0018
2.208	30.5977	205800	2.2763	0.0018
2.207	30.7226	206640	2.2677	0.0018
2.2054	30.8475	207480	2.2717	0.0018
2.2063	30.9723	208320	2.2770	0.0018
2.2045	31.0972	209160	2.2580	0.0018
2.1999	31.2221	210000	2.2613	0.0018
2.2027	31.3470	210840	2.2622	0.0018
2.2046	31.4719	211680	2.2637	0.0018
2.2022	31.5968	212520	2.2596	0.0018
2.199	31.7217	213360	2.2664	0.0018
2.1969	31.8466	214200	2.2601	0.0018
2.2006	31.9715	215040	2.2599	0.0018

Framework versions

Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1

yosefw/modernbert-medium-amharic-32k

modernbert-medium-amharic-32k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Seed this model