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swiftformer-xs-dmae-va-U-40

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metadata
base_model: MBZUAI/swiftformer-xs
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: swiftformer-xs-dmae-va-U-40
    results: []

swiftformer-xs-dmae-va-U-40

This model is a fine-tuned version of MBZUAI/swiftformer-xs on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6423
  • Accuracy: 0.8165

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.9 7 1.3883 0.3211
1.4011 1.94 15 1.3383 0.3578
1.3646 2.97 23 1.2802 0.4404
1.315 4.0 31 1.2194 0.4495
1.315 4.9 38 1.1718 0.5229
1.2634 5.94 46 1.1279 0.5046
1.1949 6.97 54 1.0761 0.5872
1.1136 8.0 62 1.0224 0.6330
1.1136 8.9 69 0.9976 0.6239
1.0824 9.94 77 0.9518 0.6606
1.0212 10.97 85 0.9117 0.6697
0.9566 12.0 93 0.8973 0.6881
0.935 12.9 100 0.8705 0.7064
0.935 13.94 108 0.8559 0.7156
0.8826 14.97 116 0.8371 0.7156
0.8688 16.0 124 0.8252 0.7156
0.8436 16.9 131 0.8211 0.6972
0.8436 17.94 139 0.8040 0.7339
0.8155 18.97 147 0.7625 0.7431
0.7831 20.0 155 0.7452 0.7431
0.7826 20.9 162 0.7279 0.7431
0.7499 21.94 170 0.7148 0.7431
0.7499 22.97 178 0.7061 0.7523
0.7539 24.0 186 0.7026 0.7523
0.7453 24.9 193 0.6819 0.7890
0.7174 25.94 201 0.6837 0.7706
0.7174 26.97 209 0.6743 0.7798
0.7083 28.0 217 0.6706 0.7798
0.6813 28.9 224 0.6644 0.8073
0.7107 29.94 232 0.6423 0.8165
0.6912 30.97 240 0.6419 0.7890
0.6912 32.0 248 0.6465 0.7890
0.7031 32.9 255 0.6346 0.8073
0.6647 33.94 263 0.6347 0.8073
0.6799 34.97 271 0.6476 0.7982
0.6799 36.0 279 0.6429 0.7982
0.6774 36.13 280 0.6518 0.7890

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1