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swadhindas324/
vit-resnet-mistral-RSICD-with-all-captioning

Name: vit-resnet-mistral-RSICD-with-all-captioning
Availability: InStock

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vit-resnet-mistral-RSICD-with-all-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	768	0.6918	80.44	0.4668	0.3027	0.2115	0.1537	0.4085	0.3975	0.4800
0.9642	2.0	1536	0.6635	80.29	0.5408	0.3874	0.2919	0.2265	0.5058	0.4766	0.8519
0.4737	3.0	2304	0.6214	83.14	0.7446	0.6301	0.5402	0.4651	0.6566	0.6537	2.3764
0.3486	4.0	3072	0.6589	84.13	0.7378	0.6198	0.5331	0.4652	0.6358	0.6415	2.3975
0.3486	5.0	3840	0.7246	83.4	0.7384	0.6197	0.5268	0.4534	0.6480	0.6368	2.3862
0.2461	6.0	4608	0.7627	84.11	0.7408	0.6209	0.5284	0.4552	0.6525	0.6414	2.4117
0.1963	7.0	5376	0.8118	83.84	0.7424	0.6242	0.5329	0.4588	0.6846	0.6590	2.4723
0.1726	8.0	6144	0.8228	84.39	0.7390	0.6157	0.5208	0.4463	0.6664	0.6440	2.4668
0.1726	9.0	6912	0.8818	84.41	0.7439	0.6279	0.5356	0.4618	0.6759	0.6530	2.4460
0.1531	10.0	7680	0.8628	84.25	0.7447	0.6229	0.5303	0.4567	0.6726	0.6516	2.4548
0.1477	11.0	8448	0.9043	83.92	0.7366	0.6208	0.5305	0.4594	0.6959	0.6585	2.5263
0.1452	12.0	9216	0.9445	83.3	0.7176	0.5943	0.4976	0.4213	0.6975	0.6536	2.3170