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swadhindas324/
vit-resnet-Mistral-UCM-without-captioning

Name: vit-resnet-Mistral-UCM-without-captioning
Availability: InStock

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vit-resnet-Mistral-UCM-without-captioning

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

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The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 64
eval_batch_size: 64
seed: 50
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: 0.1
num_epochs: 128
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Bleu-1	Bleu-2	Bleu-3	Bleu-4	Meteor	Rouge-l	Cider
No log	1.0	148	0.8694	72.16	0.4201	0.2885	0.2121	0.1576	0.3268	0.3568	0.3482
No log	2.0	296	0.7337	72.09	0.4549	0.3411	0.2676	0.2190	0.3459	0.3951	0.9703
No log	3.0	444	0.5817	73.0	0.8171	0.7561	0.7059	0.6608	0.7903	0.7816	3.1985
No log	4.0	592	0.5824	73.44	0.8470	0.7850	0.7319	0.6818	0.8122	0.7987	3.3088
No log	5.0	740	0.6066	73.08	0.8384	0.7845	0.7383	0.6968	0.8061	0.8056	3.3946
No log	6.0	888	0.6240	74.03	0.8132	0.7575	0.7093	0.6653	0.8057	0.7870	3.2903
0.6495	7.0	1036	0.6322	74.79	0.8606	0.8126	0.7716	0.7336	0.8265	0.8258	3.6389
0.6495	8.0	1184	0.6578	74.21	0.8321	0.7752	0.7286	0.6855	0.7940	0.7905	3.3892
0.6495	9.0	1332	0.6693	74.99	0.8619	0.8089	0.7623	0.7196	0.8395	0.8301	3.6491
0.6495	10.0	1480	0.6953	74.75	0.8363	0.7809	0.7344	0.6931	0.8184	0.8039	3.2834
0.6495	11.0	1628	0.7149	73.53	0.8304	0.7672	0.7147	0.6654	0.8185	0.7970	3.3121
0.6495	12.0	1776	0.7070	73.92	0.8495	0.7921	0.7402	0.6900	0.8327	0.8212	3.3830
0.6495	13.0	1924	0.7256	74.22	0.8401	0.7871	0.7398	0.6976	0.8225	0.8149	3.3926
0.2972	14.0	2072	0.7378	74.92	0.8563	0.8033	0.7577	0.7157	0.8298	0.8130	3.4087
0.2972	15.0	2220	0.7139	74.88	0.8503	0.7923	0.7452	0.7012	0.8294	0.8170	3.6068
0.2972	16.0	2368	0.7602	74.52	0.8419	0.7828	0.7319	0.6849	0.8308	0.8127	3.4385
0.2972	17.0	2516	0.7660	75.12	0.8660	0.8103	0.7630	0.7182	0.8403	0.8293	3.4620
0.2972	18.0	2664	0.7953	73.5	0.8262	0.7652	0.7161	0.6703	0.8137	0.7977	3.2445
0.2972	19.0	2812	0.7841	74.36	0.8311	0.7702	0.7191	0.6729	0.8202	0.8041	3.3607