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swadhindas324/
vit-resnet-mistral-NWPU-with-7-captioning

Name: vit-resnet-mistral-NWPU-with-7-captioning
Availability: InStock

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vit-resnet-mistral-NWPU-with-7-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
0.5079	1.0	2215	0.4756	82.99	0.5062	0.3499	0.2396	0.1568	0.4183	0.3744	0.1308
0.4044	2.0	4430	0.3607	84.9	0.8150	0.7062	0.6219	0.5546	0.7145	0.6993	1.5802
0.3306	3.0	6645	0.3248	85.09	0.8278	0.7298	0.6519	0.5888	0.7408	0.7296	1.6979
0.2994	4.0	8860	0.3135	85.57	0.8583	0.7733	0.7018	0.6424	0.7701	0.7573	1.7737
0.2812	5.0	11075	0.3097	85.76	0.8678	0.7822	0.7128	0.6560	0.7736	0.7652	1.8122
0.2659	6.0	13290	0.3106	85.64	0.8562	0.7682	0.6967	0.6383	0.7781	0.7620	1.8217
0.2596	7.0	15505	0.3154	86.19	0.8602	0.7745	0.7060	0.6503	0.7768	0.7632	1.8264
0.2488	8.0	17720	0.3207	86.16	0.8655	0.7822	0.7135	0.6575	0.7791	0.7689	1.8329
0.2384	9.0	19935	0.3241	86.13	0.8677	0.7831	0.7117	0.6528	0.7855	0.7736	1.8159
0.2285	10.0	22150	0.3306	86.03	0.8594	0.7749	0.7056	0.6488	0.7754	0.7660	1.8252
0.2187	11.0	24365	0.3379	86.21	0.8648	0.7787	0.7084	0.6510	0.7817	0.7680	1.8212
0.2090	12.0	26580	0.3485	86.25	0.8608	0.7730	0.7014	0.6438	0.7705	0.7618	1.7850
0.2150	13.0	28795	0.3529	86.3	0.8582	0.7702	0.6975	0.6379	0.7674	0.7544	1.7825
0.2034	14.0	31010	0.3639	86.29	0.8596	0.7713	0.6995	0.6409	0.7597	0.7542	1.7632