prodm93 / twiiter-image-sentiment-resnet50-ft

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Total runs: 2
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: March 18 2025
image-classification

Introduction of twiiter-image-sentiment-resnet50-ft

Model Details of twiiter-image-sentiment-resnet50-ft

img_twitter_test

This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0959
  • Accuracy: 0.3604
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: 0.1
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.1706 1.0 61 1.1410 0.3737
1.108 2.0 122 1.0930 0.3470
1.1057 3.0 183 1.1984 0.3439
1.0956 4.0 244 1.0968 0.3491
1.0959 5.0 305 1.0959 0.3604
Framework versions
  • Transformers 4.49.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.4.1
  • Tokenizers 0.21.1

Runs of prodm93 twiiter-image-sentiment-resnet50-ft on huggingface.co

2
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twiiter-image-sentiment-resnet50-ft is an open source model from GitHub that offers a free installation service, and any user can find twiiter-image-sentiment-resnet50-ft on GitHub to install. At the same time, huggingface.co provides the effect of twiiter-image-sentiment-resnet50-ft install, users can directly use twiiter-image-sentiment-resnet50-ft installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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Updated:July 05 2022