optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 0.02, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
9.3368	5.6757	0
5.5627	5.5987	1
5.5311	5.5419	2
5.5152	5.5201	3
5.5005	5.6477	4
5.4704	5.5914	5
5.4610	6.0922	6
5.4584	5.7137	7
5.4528	5.8658	8
5.4820	5.5628	9
5.4874	5.5309	10
5.4917	5.7595	11
5.4898	5.7333	12
5.4833	5.6789	13
5.4767	5.9588	14
5.4883	5.9895	15
5.4694	6.0100	16
5.4663	6.0316	17
5.4602	5.9233	18
5.4576	6.0051	19
5.4559	5.9966	20
5.4651	6.0025	21
5.4660	6.0160	22
5.4626	5.8324	23
5.4647	5.8383	24
5.4695	6.0272	25
5.4614	6.0724	26
5.4623	5.9454	27
5.4678	6.0196	28
5.4860	5.5949	29
5.4851	5.8838	30
5.4666	5.8506	31
5.4715	6.0391	32
5.4630	6.0870	33
5.4646	6.2195	34
5.4574	5.9696	35
5.4564	5.8970	36
5.4570	5.9522	37
5.4559	6.1518	38
5.4584	6.1860	39
5.4732	6.1168	40
5.4625	6.1588	41
5.4601	5.9868	42
5.4645	5.9606	43
5.4664	6.1495	44
5.4698	6.0152	45
5.4666	6.2713	46
5.4557	6.2708	47
5.4557	6.0003	48
5.4693	5.9321	49
5.4928	5.8971	50
5.5032	6.0766	51
5.4749	5.8919	52
5.4689	5.9853	53
5.4665	5.9329	54
5.4574	5.9770	55
5.4686	6.1022	56
5.4727	5.8973	57
5.4692	5.9633	58
5.4608	6.0480	59
5.4613	5.9596	60
5.4607	6.1158	61
5.4531	6.0617	62
5.4610	6.0375	63
5.4631	6.1184	64
5.4627	6.0465	65
5.4685	6.0011	66
5.4642	6.0828	67
5.4577	6.0883	68
5.4615	5.9523	69
5.4673	5.7216	70
5.4724	6.0274	71
5.4601	6.0344	72
5.4640	5.9661	73
5.4590	6.0013	74
5.4622	6.0172	75
5.4666	5.8407	76
5.4669	6.0261	77
5.4859	5.9295	78
5.5042	6.1254	79
5.4845	5.8930	80
5.5001	5.8867	81
5.4923	5.9480	82
5.4909	6.0475	83
5.4780	5.9289	84
5.4867	5.8134	85
5.4877	6.0032	86
5.4806	6.0884	87
5.4784	6.0567	88
5.4830	5.9790	89
5.4894	5.8919	90
5.4890	5.9626	91
5.4774	6.0267	92
5.5033	6.1150	93
5.4765	5.9776	94
5.4657	6.1395	95
5.4720	5.9938	96
5.4748	5.9656	97
5.4701	6.0163	98
5.4718	6.1462	99
5.4672	6.0804	100
5.4775	6.1055	101
5.4775	6.0936	102
5.4673	5.9839	103
5.4691	5.8972	104
5.4694	5.8271	105
5.5106	5.5305	106
5.5135	5.8806	107
5.4786	6.1380	108
5.4770	5.9899	109
5.4709	6.1072	110
5.4701	5.9356	111
5.4636	5.8304	112
5.4670	6.0451	113
5.4598	6.0311	114
5.4731	5.9862	115
5.4798	5.9589	116
5.4674	5.9356	117
5.4634	6.0088	118
5.4709	5.9534	119
5.4891	5.9995	120
5.4737	5.8611	121
5.4725	6.0112	122
5.4835	5.6280	123
5.5217	5.6917	124
5.4821	5.9458	125
5.4898	5.7593	126
5.4866	5.9110	127
5.4744	5.9463	128
5.4673	6.0359	129
5.4838	6.0166	130
5.4864	6.0046	131
5.4896	5.9479	132
5.4722	6.0699	133
5.4627	6.0684	134
5.4690	6.0577	135
5.4666	6.1473	136
5.4655	6.0441	137
5.4665	5.9313	138
5.4588	6.1375	139
5.4575	6.1655	140
5.4609	5.9701	141
5.4666	6.0677	142
5.4672	6.1272	143
5.4776	6.2186	144
5.4769	5.9815	145
5.4666	6.0674	146
5.4670	6.0282	147
5.4868	5.7416	148
5.4901	6.0836	149
5.4877	5.9086	150
5.4842	5.8724	151
5.5167	5.7298	152
5.5043	5.7802	153
5.4737	6.0805	154
5.4805	6.0888	155
5.4765	5.9967	156
5.4691	5.9332	157
5.4697	6.0675	158
5.4648	6.0689	159
5.4658	5.9954	160
5.4721	5.8917	161
5.4641	5.8973	162
5.4703	6.0126	163
5.4753	5.9064	164
5.4731	6.0835	165
5.5094	5.5720	166
5.5355	5.9077	167
5.4791	6.0669	168
5.4690	6.0729	169
5.4635	5.9580	170
5.4698	6.1453	171
5.4668	5.9952	172
5.4728	6.0041	173
5.5062	6.1592	174
5.4944	5.9536	175
5.4802	5.9673	176
5.4710	5.9888	177
5.4653	6.0656	178
5.4618	6.0278	179
5.4659	5.9563	180
5.4596	6.0022	181
5.4627	5.9594	182
5.4688	5.8462	183
5.4662	5.9550	184
5.4646	5.9757	185
5.4753	5.9400	186
5.4911	5.7438	187
5.4681	6.0941	188
5.4719	6.0324	189
5.4692	6.0313	190
5.4634	5.9874	191
5.4639	5.9928	192
5.4714	6.0265	193
5.4569	5.8387	194
5.4606	6.0462	195
5.4667	5.9636	196
5.4653	6.0299	197
5.4623	6.0311	198
5.4629	5.9745	199
5.4630	5.9398	200
5.4618	5.9005	201
5.4611	5.8718	202
5.4979	5.7893	203
5.4995	5.8556	204
5.4949	5.9533	205
5.4806	6.0033	206
5.4700	6.0395	207
5.4601	6.0592	208
5.4605	6.1408	209
5.4638	6.0469	210
5.4592	6.1216	211
5.4646	6.0284	212
5.4607	5.8940	213
5.4573	5.8946	214
5.4690	5.8057	215
5.5077	5.8491	216
5.4734	5.9847	217
5.4859	5.9075	218
5.4889	6.0483	219
5.4837	6.0959	220
5.4878	5.9962	221
5.4854	5.9575	222
5.4763	6.0648	223
5.4890	5.9731	224
5.4866	5.9771	225
5.4906	5.8407	226
5.4735	5.9678	227
5.4777	5.9756	228
5.4718	6.2007	229
5.5181	6.2549	230
5.4902	5.9385	231
5.4804	5.8927	232
5.4670	5.9336	233
5.4641	6.0430	234
5.4797	5.9510	235
5.4735	6.0544	236
5.4720	6.1127	237
5.4669	5.9939	238
5.4735	6.0469	239
5.4671	6.0462	240
5.4701	5.9689	241
5.4629	6.1712	242
5.4697	5.8240	243
5.4705	5.9930	244
5.4638	5.9622	245
5.4558	6.0722	246
5.4628	5.9254	247
5.5040	5.5639	248
5.5086	5.6835	249
5.4892	5.8721	250
5.4737	5.7408	251
5.4715	5.7788	252
5.4698	6.0910	253
5.4714	6.0434	254
5.4702	5.9299	255
5.4653	5.8748	256
5.4639	5.9960	257
5.4674	5.9360	258
5.4700	5.8395	259
5.4724	5.9795	260
5.4697	5.9666	261
5.4753	6.0311	262
5.4763	6.2138	263
5.4732	5.9983	264
5.4672	6.1064	265
5.4640	6.1435	266
5.4687	6.0045	267
5.4682	5.9584	268
5.4629	5.8993	269
5.4575	5.9650	270
5.4612	5.9068	271
5.4643	5.8807	272
5.4904	6.1078	273
5.4683	6.0270	274
5.4759	5.9261	275
5.4712	6.0527	276
5.4673	5.9386	277
5.4624	6.0371	278
5.4631	6.0731	279
5.4628	6.1382	280
5.4681	6.0160	281
5.4631	6.0364	282
5.4745	6.1409	283
5.4783	5.9656	284
5.4972	5.8866	285
5.4840	5.9830	286
5.4811	5.9043	287
5.4728	6.0377	288
5.4732	5.9237	289
5.4851	6.2526	290
5.4867	5.8407	291
5.4796	6.1529	292
5.4948	5.7028	293
5.4849	5.9857	294
5.4844	6.0176	295
5.4786	6.0555	296
5.4669	6.0944	297
5.4658	6.1695	298
5.4630	6.0527	299
5.4640	6.0363	300
5.4657	6.0326	301
5.4641	6.0652	302
5.4697	6.1227	303
5.4632	6.0833	304
5.4589	6.3688	305
5.4627	5.9862	306
5.4695	5.9722	307
5.4629	6.1108	308
5.4686	5.9089	309
5.4580	6.2293	310
5.4608	5.9682	311
5.4715	5.9653	312
5.4710	6.2234	313
5.4719	6.1679	314
5.4841	5.7812	315
5.4806	5.7937	316
5.4864	5.8997	317
5.4724	5.9115	318
5.4691	5.9373	319
5.4752	6.0193	320
5.4800	6.0091	321
5.4766	6.0992	322
5.4684	6.0849	323
5.4689	5.9258	324
5.4670	6.0871	325
5.4678	6.0564	326
5.4651	5.9685	327
5.4649	6.0744	328
5.4651	6.1406	329

Framework versions

Transformers 4.40.2
TensorFlow 2.15.0
Datasets 2.19.1
Tokenizers 0.19.1