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bigmorning/
whisper_charsplit_new_round4__0035

Name: whisper_charsplit_new_round4__0035
Availability: InStock

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whisper_charsplit_new_round4__0035

This model is a fine-tuned version of bigmorning/whisper_charsplit_new_round2__0061 on an unknown dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32

Train Loss	Train Accuracy	Train Wermet	Validation Loss	Validation Accuracy	Validation Wermet	Epoch
0.0009	0.0795	7.9702	0.5713	0.0770	6.9300	0
0.0011	0.0795	7.7485	0.5743	0.0771	6.6465	1
0.0011	0.0795	8.1600	0.5748	0.0771	7.1363	2
0.0008	0.0795	8.1954	0.5845	0.0770	7.1869	3
0.0009	0.0795	8.4533	0.5771	0.0771	7.4112	4
0.0009	0.0795	8.3048	0.5912	0.0770	6.5276	5
0.0008	0.0795	8.2183	0.5810	0.0771	7.1210	6
0.0011	0.0795	8.3785	0.5861	0.0770	7.6613	7
0.0010	0.0795	8.0860	0.5811	0.0771	7.0809	8
0.0009	0.0795	8.2523	0.5894	0.0770	7.1269	9
0.0006	0.0795	8.7530	0.5819	0.0771	7.3657	10
0.0007	0.0795	8.5391	0.5773	0.0771	7.7370	11
0.0010	0.0795	8.8222	0.5894	0.0770	7.9252	12
0.0014	0.0795	8.9039	0.5880	0.0771	7.6404	13
0.0009	0.0795	8.6866	0.5777	0.0771	7.5804	14
0.0006	0.0795	9.0833	0.5736	0.0772	8.3242	15
0.0003	0.0795	9.3697	0.5732	0.0772	8.4795	16
0.0006	0.0795	9.4161	0.5838	0.0771	8.5173	17
0.0011	0.0795	9.7801	0.5967	0.0769	8.5462	18
0.0016	0.0795	9.9252	0.5824	0.0771	8.8226	19
0.0009	0.0795	10.1258	0.5813	0.0771	8.6993	20
0.0006	0.0795	9.8897	0.5784	0.0772	8.1699	21
0.0009	0.0795	9.3199	0.5971	0.0771	7.6986	22
0.0018	0.0795	10.2724	0.5924	0.0769	8.9443	23
0.0012	0.0795	9.5275	0.5783	0.0771	7.7057	24
0.0010	0.0795	8.6555	0.5738	0.0772	7.1508	25
0.0005	0.0795	8.8172	0.5775	0.0772	6.9496	26
0.0005	0.0795	8.4569	0.5860	0.0771	7.5262	27
0.0012	0.0795	9.6634	0.5917	0.0770	8.3290	28
0.0011	0.0795	8.9484	0.5855	0.0771	7.6950	29
0.0007	0.0795	8.7377	0.5882	0.0771	7.4076	30
0.0005	0.0795	8.5209	0.5855	0.0772	6.7134	31
0.0009	0.0795	8.5136	0.5862	0.0771	8.0204	32
0.0011	0.0795	7.8920	0.5788	0.0772	7.3091	33
0.0008	0.0795	8.8453	0.5776	0.0772	7.0827	34