salt_language_ID

This model is a fine-tuned version of google/t5-efficient-tiny on the generator dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

learning_rate: 0.001
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
training_steps: 20000

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.9948	0.025	500	0.7153	0.1757
0.3269	0.05	1000	0.7217	0.2611
0.2853	0.075	1500	0.9151	0.2412
0.1823	0.1	2000	0.5561	0.3965
0.1953	0.125	2500	0.5975	0.3824
0.1831	0.15	3000	0.5670	0.4264
0.141	0.175	3500	0.7885	0.3443
0.1081	0.2	4000	0.8961	0.3111
0.154	0.225	4500	0.7975	0.3491
0.1306	0.25	5000	0.4824	0.5092
0.1013	0.275	5500	0.4946	0.4613
0.1083	0.3	6000	0.6959	0.4038
0.1121	0.325	6500	0.6938	0.4004
0.1168	0.35	7000	0.7787	0.3948
0.1202	0.375	7500	0.5420	0.4975
0.1169	0.4	8000	0.5099	0.5128
0.1119	0.425	8500	0.5815	0.4582
0.1258	0.45	9000	0.5103	0.5002
0.0878	0.475	9500	0.5189	0.5089
0.1032	0.5	10000	0.4365	0.5674
0.0854	0.525	10500	0.5854	0.5176
0.1028	0.55	11000	0.5167	0.5253
0.0853	0.575	11500	0.4268	0.5922
0.0716	0.6	12000	0.5486	0.5204
0.0771	0.625	12500	0.4643	0.5532
0.0613	0.65	13000	0.5525	0.5050
0.0819	0.675	13500	0.4500	0.5953
0.0785	0.7	14000	0.5016	0.5245
0.079	0.725	14500	0.4453	0.5789
0.0749	0.75	15000	0.4218	0.5866
0.0749	0.775	15500	0.4208	0.6114
0.0655	0.8	16000	0.4203	0.6133
0.077	0.825	16500	0.4446	0.5891
0.0516	0.85	17000	0.4239	0.5985
0.0555	0.875	17500	0.4040	0.6237
0.0622	0.9	18000	0.4575	0.5978
0.0752	0.925	18500	0.4257	0.5959
0.0555	0.95	19000	0.4462	0.5997
0.0646	0.975	19500	0.4225	0.6124
0.0676	1.0	20000	0.4200	0.6086