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swadhindas324/
vit-resnet-mistral-NWPU-with-9-captioning

Name: vit-resnet-mistral-NWPU-with-9-captioning
Availability: InStock

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vit-resnet-mistral-NWPU-with-9-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
0.5099	1.0	2215	0.4779	83.09	0.5057	0.3498	0.2403	0.1583	0.4196	0.3753	0.1382
0.4064	2.0	4430	0.3626	84.88	0.8192	0.7121	0.6286	0.5622	0.7127	0.6992	1.5975
0.3323	3.0	6645	0.3265	85.04	0.8296	0.7325	0.6546	0.5912	0.7427	0.7325	1.7041
0.3007	4.0	8860	0.3149	85.53	0.8624	0.7783	0.7082	0.6504	0.7720	0.7605	1.7888
0.2822	5.0	11075	0.3109	85.77	0.8667	0.7810	0.7112	0.6540	0.7717	0.7648	1.8148
0.2671	6.0	13290	0.3127	85.68	0.8596	0.7718	0.7000	0.6415	0.7791	0.7638	1.8211
0.2605	7.0	15505	0.3154	86.18	0.8680	0.7846	0.7160	0.6594	0.7802	0.7693	1.8508
0.2494	8.0	17720	0.3216	86.3	0.8656	0.7823	0.7135	0.6570	0.7701	0.7631	1.8297
0.2390	9.0	19935	0.3253	86.34	0.8758	0.7922	0.7207	0.6614	0.7822	0.7754	1.8444
0.2295	10.0	22150	0.3323	86.37	0.8696	0.7848	0.7146	0.6573	0.7740	0.7671	1.8537
0.2193	11.0	24365	0.3399	86.57	0.8742	0.7889	0.7176	0.6592	0.7758	0.7688	1.8497
0.2095	12.0	26580	0.3489	86.43	0.8656	0.7778	0.7061	0.6486	0.7591	0.7557	1.7879
0.2152	13.0	28795	0.3549	86.74	0.8720	0.7861	0.7150	0.6560	0.7620	0.7607	1.8101
0.2040	14.0	31010	0.3628	86.68	0.8737	0.7898	0.7205	0.6634	0.7625	0.7632	1.8298