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

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

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vit-convnext-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
0.5112	1.0	2215	0.4784	83.04	0.5093	0.3454	0.2357	0.1577	0.4238	0.3784	0.1341
0.4061	2.0	4430	0.3642	84.74	0.8233	0.7162	0.6331	0.5668	0.7065	0.6984	1.5828
0.3342	3.0	6645	0.3277	85.05	0.8313	0.7336	0.6556	0.5925	0.7418	0.7316	1.7291
0.3022	4.0	8860	0.3158	85.6	0.8661	0.7829	0.7127	0.6539	0.7717	0.7611	1.7960
0.2836	5.0	11075	0.3120	85.72	0.8691	0.7841	0.7149	0.6578	0.7641	0.7636	1.8338
0.2682	6.0	13290	0.3132	85.9	0.8667	0.7788	0.7074	0.6491	0.7744	0.7655	1.8381
0.2615	7.0	15505	0.3169	86.5	0.8797	0.7983	0.7310	0.6762	0.7781	0.7745	1.8934
0.2505	8.0	17720	0.3225	86.52	0.8732	0.7908	0.7220	0.6648	0.7706	0.7678	1.8529
0.2396	9.0	19935	0.3271	86.57	0.8781	0.7948	0.7233	0.6626	0.7703	0.7705	1.8351
0.2298	10.0	22150	0.3349	86.63	0.8776	0.7946	0.7267	0.6707	0.7645	0.7667	1.8733
0.2197	11.0	24365	0.3402	86.78	0.8818	0.7979	0.7292	0.6719	0.7709	0.7695	1.8716
0.2106	12.0	26580	0.3492	86.72	0.8773	0.7942	0.7252	0.6687	0.7626	0.7661	1.8342