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

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

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vit-resnet-mistral-NWPU-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
0.5110	1.0	2215	0.4791	82.96	0.5074	0.3514	0.2409	0.1581	0.4196	0.3751	0.1387
0.4072	2.0	4430	0.3636	85.09	0.8288	0.7234	0.6415	0.5755	0.7099	0.7028	1.6152
0.3328	3.0	6645	0.3269	85.35	0.8371	0.7382	0.6587	0.5943	0.7362	0.7313	1.7254
0.3010	4.0	8860	0.3149	85.72	0.8727	0.7882	0.7167	0.6568	0.7645	0.7583	1.7931
0.2824	5.0	11075	0.3105	86.03	0.8788	0.7954	0.7267	0.6698	0.7707	0.7698	1.8582
0.2669	6.0	13290	0.3117	86.02	0.8713	0.7859	0.7151	0.6569	0.7720	0.7656	1.8524
0.2603	7.0	15505	0.3175	86.59	0.8819	0.7999	0.7323	0.6762	0.7728	0.7726	1.9148
0.2491	8.0	17720	0.3210	86.68	0.8803	0.7990	0.7315	0.6757	0.7651	0.7684	1.8606
0.2384	9.0	19935	0.3250	86.64	0.8915	0.8102	0.7395	0.6804	0.7740	0.7762	1.8764
0.2286	10.0	22150	0.3344	86.76	0.8765	0.7930	0.7236	0.6658	0.7506	0.7585	1.8450
0.2186	11.0	24365	0.3377	86.87	0.8861	0.8036	0.7343	0.6764	0.7669	0.7710	1.8890
0.2085	12.0	26580	0.3516	86.83	0.8812	0.7974	0.7277	0.6711	0.7578	0.7645	1.8529
0.2143	13.0	28795	0.3558	87.03	0.8771	0.7948	0.7238	0.6643	0.7589	0.7641	1.8520
0.2032	14.0	31010	0.3640	86.81	0.8749	0.7886	0.7170	0.6587	0.7536	0.7570	1.8091