CoolFace
Modelpublic

swadhindas324/convnext-Mistral-RSICD-without-captioning

sourceHugging Faceupdated 2mo agoView on Hugging Face
0likes3downloads
Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

convnext-Mistral-RSICD-without-captioning

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.7262
  • —Accuracy: 82.42
  • —Bleu-1: 0.6502
  • —Bleu-2: 0.5182
  • —Bleu-3: 0.4283
  • —Bleu-4: 0.3617
  • —Meteor: 0.6100
  • —Rouge-l: 0.5789
  • —Cider: 1.9325

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 0.0001
  • —trainbatchsize: 64
  • —evalbatchsize: 64
  • —seed: 50
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 0.1
  • —num_epochs: 128
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyBleu-1Bleu-2Bleu-3Bleu-4MeteorRouge-lCider
No log1.07681.356779.430.51590.35050.25260.18740.45930.44960.6915
2.42852.015361.293979.720.57310.42670.32870.25510.54970.51401.1645
0.94113.023041.252281.950.68640.56380.46960.39480.67230.62122.1220
0.74874.030721.326782.150.68960.56740.47180.39620.68220.63522.1771
0.74875.038401.417181.50.65430.52720.43490.36630.64250.59171.9704
0.53416.046081.531181.760.64210.51070.41770.34880.62000.57421.9267
0.41477.053761.618481.190.62320.49060.39630.32640.61320.55811.7155
0.35728.061441.679581.160.61540.48230.38710.31680.60090.54901.7236
0.35729.069121.726282.420.65020.51820.42830.36170.61000.57891.9325

Framework versions

  • —Transformers 5.12.1
  • —Pytorch 2.12.1+cu130
  • —Datasets 5.0.0
  • —Tokenizers 0.22.2