learning_rate: 2.4e-05
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.5151	0.0091	1	1.2957	98.1381	39.1342
1.4223	0.0182	2	1.0260	98.4559	38.1078
1.1098	0.0273	3	1.0013	94.0054	35.7326
1.1589	0.0364	4	0.9531	89.1462	34.6602
1.0206	0.0455	5	0.8853	88.4196	32.4561
1.0205	0.0545	6	0.8350	96.6848	35.4300
0.8906	0.0636	7	0.7843	98.0926	34.2523
0.8454	0.0727	8	0.7538	105.2679	37.1932
0.7052	0.0818	9	0.7200	97.5477	32.0218
0.8077	0.0909	10	0.6945	95.0954	33.0745
0.8001	0.1	11	0.6633	98.8647	34.7260
0.608	0.1091	12	0.6531	88.9192	28.7387
0.6408	0.1182	13	0.6294	77.0209	24.0674
0.5705	0.1273	14	0.6226	82.4705	25.9491
0.698	0.1364	15	0.6215	88.6921	27.4887
0.6739	0.1455	16	0.6143	91.0082	27.0149
0.6492	0.1545	17	0.6050	88.7829	26.5544
0.5292	0.1636	18	0.5786	77.0209	23.3107
0.6971	0.1727	19	0.5763	73.8420	23.1923
0.6909	0.1818	20	0.5665	74.5686	24.2121
0.5823	0.1909	21	0.5549	74.9773	23.6397
0.6172	0.2	22	0.5601	81.4260	24.1858
0.5107	0.2091	23	0.5822	96.2307	28.2913
0.6271	0.2182	24	0.5797	91.1898	26.4754
0.5874	0.2273	25	0.5632	87.4659	27.0281
0.6406	0.2364	26	0.5535	77.5658	25.1924
0.6504	0.2455	27	0.5446	73.3878	22.6660
0.5805	0.2545	28	0.5492	75.1589	24.3174
0.708	0.2636	29	0.5452	79.1553	25.2319
0.7144	0.2727	30	0.5399	80.6540	24.0608
0.5303	0.2818	31	0.5443	83.8329	26.6794
0.5376	0.2909	32	0.5349	82.4251	24.4161
0.519	0.3	33	0.5362	87.4659	26.8965
0.4692	0.3091	34	0.5440	84.4687	24.8043
0.5351	0.3182	35	0.5494	80.9264	22.8831
0.5826	0.3273	36	0.5474	82.1072	23.5476
0.5443	0.3364	37	0.5406	78.7466	23.3371
0.4789	0.3455	38	0.5348	80.6540	22.7647
0.558	0.3545	39	0.5287	85.6494	23.8568
0.6398	0.3636	40	0.5198	80.3815	22.7318
0.5281	0.3727	41	0.5180	76.9301	22.7844
0.5727	0.3818	42	0.5171	77.4296	24.2055
0.5415	0.3909	43	0.5162	74.7048	23.5213
0.5421	0.4	44	0.5152	79.3370	23.6726
0.542	0.4091	45	0.5143	86.3760	24.8766
0.5253	0.4182	46	0.5127	86.6485	23.5147
0.5686	0.4273	47	0.5073	83.1063	22.6725
0.4648	0.4364	48	0.5006	82.9246	23.8568
0.472	0.4455	49	0.4944	74.7502	22.2383
0.4923	0.4545	50	0.4942	73.1608	21.6988
0.521	0.4636	51	0.4966	72.5250	21.5343
0.572	0.4727	52	0.4921	70.1181	20.5540
0.5497	0.4818	53	0.4922	72.7520	22.1265
0.4572	0.4909	54	0.4981	71.8892	22.3502
0.5089	0.5	55	0.4999	75.2498	22.4159
0.5494	0.5091	56	0.4969	80.2452	22.4028
0.4723	0.5182	57	0.5006	81.7893	21.9093
0.5199	0.5273	58	0.5035	85.1499	22.8568
0.5321	0.5364	59	0.4986	78.5195	21.9751
0.5018	0.5455	60	0.4935	75.5223	21.9686
0.5275	0.5545	61	0.4928	72.5250	21.4422
0.4819	0.5636	62	0.4961	73.5695	21.5672
0.6083	0.5727	63	0.4996	77.8837	22.0343
0.566	0.5818	64	0.4985	81.1081	22.4291
0.4821	0.5909	65	0.4940	78.9737	21.6922
0.4364	0.6	66	0.4870	77.9292	22.4159
0.4326	0.6091	67	0.4851	74.7502	22.1001
0.4776	0.6182	68	0.4885	73.4332	21.5409
0.439	0.6273	69	0.4913	75.1135	22.3107
0.5441	0.6364	70	0.4857	79.4278	22.9884
0.5194	0.6455	71	0.4796	79.3370	22.5475
0.4168	0.6545	72	0.4752	77.7475	21.8435
0.5378	0.6636	73	0.4751	75.8401	21.3106
0.5594	0.6727	74	0.4764	73.8874	21.0540
0.4448	0.6818	75	0.4720	72.6158	20.6987
0.4281	0.6909	76	0.4665	70.8447	20.6987
0.413	0.7	77	0.4686	69.7548	20.5803
0.5705	0.7091	78	0.4728	69.1644	20.2513
0.4756	0.7182	79	0.4717	68.6194	20.0934
0.5365	0.7273	80	0.4706	69.7094	19.9618
0.5304	0.7364	81	0.4701	80.8810	24.8174
0.5177	0.7455	82	0.4686	82.6975	25.2648
0.5528	0.7545	83	0.4660	78.4741	23.0673
0.5157	0.7636	84	0.4639	71.8892	20.8632
0.5247	0.7727	85	0.4611	70.2089	21.1132
0.4346	0.7818	86	0.4598	69.8456	21.4751
0.4217	0.7909	87	0.4607	70.7084	21.8501
0.4727	0.8	88	0.4627	76.3397	22.9620
0.5351	0.8091	89	0.4635	73.7965	21.7777
0.4175	0.8182	90	0.4621	71.1172	20.9027
0.5384	0.8273	91	0.4611	72.2525	21.7054
0.4353	0.8364	92	0.4628	73.1608	21.8106
0.4945	0.8455	93	0.4656	70.7993	20.6066
0.4006	0.8545	94	0.4682	70.8447	20.3237
0.4586	0.8636	95	0.4718	72.4342	20.4027
0.4737	0.8727	96	0.4760	75.2044	20.6527
0.5742	0.8818	97	0.4793	77.3842	22.3567
0.5196	0.8909	98	0.4733	76.9301	22.3699
0.4698	0.9	99	0.4611	77.1117	23.4292
0.4354	0.9091	100	0.4529	72.3433	21.0869
0.4695	0.9182	101	0.4498	73.5241	22.0607
0.4968	0.9273	102	0.4498	73.5695	22.0936
0.4859	0.9364	103	0.4494	73.0245	21.6462
0.5265	0.9455	104	0.4472	74.3869	22.1791
0.4245	0.9545	105	0.4470	74.7502	22.2975
0.4831	0.9636	106	0.4491	77.9292	23.2647
0.5879	0.9727	107	0.4521	80.5177	23.6068
0.4707	0.9818	108	0.4570	82.6521	23.7187
0.4407	0.9909	109	0.4606	82.1072	23.2252
0.4424	1.0	110	0.4605	80.6994	22.3633
0.3037	1.0091	111	0.4539	80.9264	23.8963
0.3281	1.0182	112	0.4488	86.6031	27.0676
0.3001	1.0273	113	0.4455	71.2080	21.5738
0.3576	1.0364	114	0.4447	69.8002	20.4290
0.3209	1.0455	115	0.4462	71.0263	20.6856
0.2753	1.0545	116	0.4525	74.7956	21.1922
0.2833	1.0636	117	0.4591	76.7938	21.1527
0.2317	1.0727	118	0.4609	74.7502	20.0803
0.271	1.0818	119	0.4593	70.9355	19.5473
0.2777	1.0909	120	0.4612	69.8910	19.4092
0.2744	1.1	121	0.4637	68.5286	19.4552
0.3335	1.1091	122	0.4650	69.3006	19.7381
0.3375	1.1182	123	0.4647	73.0699	20.4816
0.247	1.1273	124	0.4653	75.0681	20.6987
0.2758	1.1364	125	0.4661	74.4323	19.9487
0.3339	1.1455	126	0.4654	75.5677	20.1197
0.3112	1.1545	127	0.4632	74.2961	20.1197
0.2965	1.1636	128	0.4608	73.2062	20.1987
0.2051	1.1727	129	0.4587	71.5259	20.0013
0.3052	1.1818	130	0.4569	70.3906	19.8500
0.2378	1.1909	131	0.4552	66.5758	19.3829
0.2784	1.2	132	0.4531	65.7584	19.4026
0.3375	1.2091	133	0.4511	66.7575	19.1986
0.27	1.2182	134	0.4480	66.3942	19.1065
0.2582	1.2273	135	0.4452	67.8474	19.2578
0.2599	1.2364	136	0.4441	69.4369	19.2578
0.2509	1.2455	137	0.4437	71.2988	19.4881
0.2661	1.2545	138	0.4440	71.5713	19.3171
0.2291	1.2636	139	0.4447	71.7075	19.2776
0.2414	1.2727	140	0.4443	70.7993	19.3500
0.314	1.2818	141	0.4436	70.4360	19.2184
0.2578	1.2909	142	0.4418	69.4823	19.2513
0.3136	1.3	143	0.4387	68.8011	19.1263
0.2557	1.3091	144	0.4367	68.2107	18.9947
0.2222	1.3182	145	0.4345	68.0291	19.0670
0.1954	1.3273	146	0.4335	68.9827	19.1263
0.2454	1.3364	147	0.4325	69.0282	18.9026
0.2448	1.3455	148	0.4313	69.3915	18.9881
0.315	1.3545	149	0.4313	69.6639	18.7315
0.3397	1.3636	150	0.4315	70.4814	18.9157
0.2566	1.3727	151	0.4310	70.7539	18.8433
0.1925	1.3818	152	0.4304	70.9809	18.8631
0.2574	1.3909	153	0.4302	70.1181	19.0078
0.2114	1.4	154	0.4303	68.6649	18.9815
0.2107	1.4091	155	0.4296	67.9837	19.0078
0.2305	1.4182	156	0.4294	67.3933	18.8894
0.2538	1.4273	157	0.4298	66.9846	18.8762
0.2773	1.4364	158	0.4300	67.6203	18.9881
0.2393	1.4455	159	0.4302	69.6185	19.2118
0.2976	1.4545	160	0.4310	69.9364	19.0934
0.2181	1.4636	161	0.4311	69.9818	19.1263
0.2298	1.4727	162	0.4317	71.4805	19.1657
0.2338	1.4818	163	0.4321	71.5259	19.0802
0.3022	1.4909	164	0.4321	71.6621	19.1526
0.211	1.5	165	0.4322	72.3433	19.2842
0.2923	1.5091	166	0.4321	71.7984	19.1789
0.2603	1.5182	167	0.4317	71.9346	19.3105
0.2537	1.5273	168	0.4309	71.5713	19.2578
0.242	1.5364	169	0.4296	70.5268	19.0934
0.2378	1.5455	170	0.4287	69.9818	19.1526
0.2532	1.5545	171	0.4269	69.8456	18.9355
0.252	1.5636	172	0.4256	69.3460	18.8368
0.2394	1.5727	173	0.4246	69.1190	18.6591
0.227	1.5818	174	0.4242	69.6639	18.7315
0.3138	1.5909	175	0.4242	69.3006	18.8368
0.1926	1.6	176	0.4241	69.7548	18.8499
0.2086	1.6091	177	0.4250	69.9364	18.9026
0.2123	1.6182	178	0.4250	70.4814	19.0013
0.2696	1.6273	179	0.4254	70.4814	18.8104
0.2635	1.6364	180	0.4252	70.6630	18.7907
0.247	1.6455	181	0.4245	70.2997	18.7447
0.2356	1.6545	182	0.4242	70.4360	18.7710
0.2581	1.6636	183	0.4232	70.0272	18.7052
0.2489	1.6727	184	0.4227	69.4369	18.8368
0.2274	1.6818	185	0.4216	69.7094	18.7973
0.2735	1.6909	186	0.4210	69.2552	18.6196
0.2644	1.7	187	0.4205	69.1644	18.5604
0.2169	1.7091	188	0.4198	69.1190	18.5604
0.2187	1.7182	189	0.4193	68.8465	18.5802
0.2864	1.7273	190	0.4186	68.3924	18.4223
0.245	1.7364	191	0.4182	68.0291	18.5144
0.2584	1.7455	192	0.4174	68.1653	18.4552
0.2695	1.7545	193	0.4170	67.9382	18.3433
0.2561	1.7636	194	0.4168	67.9382	18.3038
0.245	1.7727	195	0.4165	67.6203	18.3499
0.2568	1.7818	196	0.4161	67.6203	18.2775
0.2569	1.7909	197	0.4158	67.5749	18.2644
0.3213	1.8	198	0.4153	67.2570	18.1986
0.2264	1.8091	199	0.4148	67.0754	18.1328
0.2109	1.8182	200	0.4149	67.2116	18.2380
0.2439	1.8273	201	0.4146	67.0300	18.1657
0.2002	1.8364	202	0.4144	67.1208	18.1722
0.2367	1.8455	203	0.4144	67.0754	18.1854
0.2499	1.8545	204	0.4141	66.8937	18.1986
0.2319	1.8636	205	0.4141	67.0754	18.1920
0.2286	1.8727	206	0.4139	66.8937	18.2644
0.2146	1.8818	207	0.4141	67.0300	18.1986
0.2515	1.8909	208	0.4142	67.3025	18.2775
0.1864	1.9	209	0.4140	67.2570	18.2117
0.2598	1.9091	210	0.4141	67.0300	18.2051
0.2524	1.9182	211	0.4141	67.2570	18.2051
0.2673	1.9273	212	0.4140	67.4387	18.3104
0.2245	1.9364	213	0.4140	67.4387	18.2183
0.2275	1.9455	214	0.4140	67.3479	18.2183
0.2464	1.9545	215	0.4140	67.4841	18.2512
0.228	1.9636	216	0.4140	67.2570	18.2315
0.2154	1.9727	217	0.4138	67.3933	18.2380
0.2563	1.9818	218	0.4140	67.1208	18.1722
0.2504	1.9909	219	0.4141	67.6203	18.2973
0.2743	2.0	220	0.4139	67.5749	18.2709

Framework versions

Transformers 4.57.3
Pytorch 2.9.1+cu128
Datasets 4.4.1
Tokenizers 0.22.1

nkkbr/whisper-large-v3-zatoichi-ja-zatoichi-TEST-5-EX-6-TRAIN_2_TO_36_data_v2_EVAL_1

Whisper Large v3 - Japanese Zatoichi ASR

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nkkbr/
whisper-large-v3-zatoichi-ja-zatoichi-TEST-5-EX-6-TRAIN_2_TO_36_data_v2_EVAL_1