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swadhindas324/
vit-resnet-mistral-NWPU-with-8-captioning

Name: vit-resnet-mistral-NWPU-with-8-captioning
Availability: InStock

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vit-resnet-mistral-NWPU-with-8-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
0.5091	1.0	2215	0.4771	82.93	0.5057	0.3496	0.2396	0.1572	0.4205	0.3746	0.1373
0.4063	2.0	4430	0.3619	84.75	0.8156	0.7072	0.6235	0.5571	0.7119	0.6972	1.5817
0.3317	3.0	6645	0.3261	85.18	0.8297	0.7325	0.6547	0.5916	0.7435	0.7319	1.7100
0.3002	4.0	8860	0.3144	85.46	0.8599	0.7745	0.7028	0.6430	0.7670	0.7563	1.7636
0.2819	5.0	11075	0.3104	85.82	0.8685	0.7834	0.7150	0.6589	0.7768	0.7685	1.8204
0.2667	6.0	13290	0.3111	85.76	0.8575	0.7699	0.6992	0.6418	0.7776	0.7635	1.8193
0.2602	7.0	15505	0.3165	86.19	0.8646	0.7804	0.7114	0.6550	0.7779	0.7662	1.8498
0.2492	8.0	17720	0.3212	86.29	0.8633	0.7800	0.7121	0.6566	0.7712	0.7649	1.8188
0.2387	9.0	19935	0.3267	86.33	0.8762	0.7921	0.7203	0.6607	0.7856	0.7775	1.8331
0.2287	10.0	22150	0.3324	86.23	0.8641	0.7798	0.7105	0.6536	0.7707	0.7639	1.8201
0.2189	11.0	24365	0.3382	86.31	0.8671	0.7809	0.7095	0.6514	0.7831	0.7704	1.8190
0.2093	12.0	26580	0.3495	86.19	0.8588	0.7698	0.6969	0.6385	0.7620	0.7546	1.7401
0.2148	13.0	28795	0.3558	86.5	0.8624	0.7748	0.7013	0.6406	0.7573	0.7526	1.7727
0.2038	14.0	31010	0.3656	86.4	0.8635	0.7771	0.7058	0.6472	0.7659	0.7598	1.7986