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

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

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vit-convnext-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	80.82	0.4668	0.3027	0.2115	0.1537	0.4085	0.3975	0.4800
0.9613	2.0	1536	0.6654	79.71	0.5529	0.3979	0.2983	0.2293	0.5204	0.4831	0.8729
0.4780	3.0	2304	0.6192	82.27	0.7396	0.6219	0.5283	0.4503	0.6811	0.6570	2.3965
0.3591	4.0	3072	0.6623	84.14	0.7501	0.6341	0.5467	0.4782	0.6538	0.6502	2.4749
0.3591	5.0	3840	0.7271	83.42	0.7515	0.6349	0.5447	0.4745	0.6772	0.6595	2.5529
0.2512	6.0	4608	0.7516	83.98	0.7486	0.6314	0.5404	0.4672	0.6669	0.6535	2.4837
0.1983	7.0	5376	0.8064	84.2	0.7431	0.6226	0.5301	0.4570	0.6838	0.6606	2.5097
0.1730	8.0	6144	0.8239	84.31	0.7464	0.6249	0.5327	0.4616	0.6873	0.6606	2.5639
0.1730	9.0	6912	0.8647	84.05	0.7409	0.6211	0.5280	0.4544	0.6862	0.6597	2.5088
0.1534	10.0	7680	0.8776	84.11	0.7358	0.6144	0.5225	0.4514	0.6954	0.6589	2.4861
0.1468	11.0	8448	0.9117	83.81	0.7241	0.6020	0.5082	0.4351	0.6807	0.6469	2.4261
0.1438	12.0	9216	0.9457	83.3	0.7206	0.5985	0.5032	0.4285	0.6909	0.6497	2.3592