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vit-msn-small-beta-fia-manually-enhanced_test_2

Image Classification
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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/vit-msn-small
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: vit-msn-small-beta-fia-manually-enhanced_test_2
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7746478873239436

vit-msn-small-beta-fia-manually-enhanced_test_2

This model is a fine-tuned version of facebook/vit-msn-small on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5203
  • Accuracy: 0.7746

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: 1e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.2
  • num_epochs: 500

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.5714 1 0.6037 0.7465
No log 1.7143 3 0.6071 0.7324
No log 2.8571 5 0.6120 0.7183
No log 4.0 7 0.6188 0.7183
No log 4.5714 8 0.6206 0.7183
0.4866 5.7143 10 0.6272 0.6972
0.4866 6.8571 12 0.6355 0.6901
0.4866 8.0 14 0.6399 0.6901
0.4866 8.5714 15 0.6364 0.6831
0.4866 9.7143 17 0.6295 0.6831
0.4866 10.8571 19 0.6288 0.6901
0.4519 12.0 21 0.6185 0.6901
0.4519 12.5714 22 0.6159 0.6901
0.4519 13.7143 24 0.6113 0.6972
0.4519 14.8571 26 0.5987 0.6901
0.4519 16.0 28 0.6017 0.6972
0.4519 16.5714 29 0.6067 0.6972
0.437 17.7143 31 0.6062 0.6620
0.437 18.8571 33 0.5966 0.6901
0.437 20.0 35 0.5858 0.7113
0.437 20.5714 36 0.5889 0.7042
0.437 21.7143 38 0.5768 0.7183
0.4353 22.8571 40 0.5752 0.7183
0.4353 24.0 42 0.5729 0.7183
0.4353 24.5714 43 0.5909 0.6972
0.4353 25.7143 45 0.6038 0.6761
0.4353 26.8571 47 0.5904 0.6901
0.4353 28.0 49 0.5847 0.6831
0.4141 28.5714 50 0.5615 0.7113
0.4141 29.7143 52 0.5544 0.7254
0.4141 30.8571 54 0.5904 0.6690
0.4141 32.0 56 0.5948 0.6831
0.4141 32.5714 57 0.5800 0.6972
0.4141 33.7143 59 0.5902 0.6972
0.4066 34.8571 61 0.5950 0.6690
0.4066 36.0 63 0.5500 0.7324
0.4066 36.5714 64 0.5470 0.7324
0.4066 37.7143 66 0.5859 0.6901
0.4066 38.8571 68 0.5955 0.6831
0.3827 40.0 70 0.5967 0.6761
0.3827 40.5714 71 0.5809 0.6901
0.3827 41.7143 73 0.5721 0.6972
0.3827 42.8571 75 0.6019 0.6831
0.3827 44.0 77 0.6071 0.6901
0.3827 44.5714 78 0.5962 0.6972
0.37 45.7143 80 0.6114 0.6831
0.37 46.8571 82 0.5594 0.7183
0.37 48.0 84 0.5493 0.7324
0.37 48.5714 85 0.5744 0.7113
0.37 49.7143 87 0.5443 0.7183
0.37 50.8571 89 0.5469 0.7324
0.3797 52.0 91 0.6003 0.6831
0.3797 52.5714 92 0.6048 0.6901
0.3797 53.7143 94 0.5203 0.7746
0.3797 54.8571 96 0.5327 0.7535
0.3797 56.0 98 0.6414 0.6338
0.3797 56.5714 99 0.6562 0.6197
0.3715 57.7143 101 0.5754 0.7183
0.3715 58.8571 103 0.5672 0.7254
0.3715 60.0 105 0.6060 0.6901
0.3715 60.5714 106 0.6536 0.6197
0.3715 61.7143 108 0.6177 0.6479
0.3483 62.8571 110 0.5385 0.7535
0.3483 64.0 112 0.5630 0.7394
0.3483 64.5714 113 0.5818 0.7254
0.3483 65.7143 115 0.6055 0.6972
0.3483 66.8571 117 0.5737 0.7324
0.3483 68.0 119 0.5606 0.7394
0.3667 68.5714 120 0.5829 0.7183
0.3667 69.7143 122 0.5931 0.7113
0.3667 70.8571 124 0.5375 0.7606
0.3667 72.0 126 0.5797 0.7113
0.3667 72.5714 127 0.6182 0.6690
0.3667 73.7143 129 0.6497 0.6690
0.3357 74.8571 131 0.6432 0.6831
0.3357 76.0 133 0.6772 0.6620
0.3357 76.5714 134 0.6395 0.6479
0.3357 77.7143 136 0.5895 0.7042
0.3357 78.8571 138 0.5921 0.6972
0.3415 80.0 140 0.5618 0.7254
0.3415 80.5714 141 0.5697 0.7183
0.3415 81.7143 143 0.6535 0.6197
0.3415 82.8571 145 0.6627 0.6338
0.3415 84.0 147 0.6194 0.6761
0.3415 84.5714 148 0.6301 0.6901
0.3296 85.7143 150 0.6436 0.6690
0.3296 86.8571 152 0.6348 0.6831
0.3296 88.0 154 0.6704 0.6479
0.3296 88.5714 155 0.7190 0.6338
0.3296 89.7143 157 0.7064 0.6338
0.3296 90.8571 159 0.6291 0.6549
0.3296 92.0 161 0.6933 0.6197
0.3296 92.5714 162 0.7115 0.6197
0.3296 93.7143 164 0.6229 0.6690
0.3296 94.8571 166 0.5727 0.7183
0.3296 96.0 168 0.5965 0.6901
0.3296 96.5714 169 0.6433 0.6690
0.3174 97.7143 171 0.6634 0.6408
0.3174 98.8571 173 0.6166 0.6549
0.3174 100.0 175 0.5896 0.6972
0.3174 100.5714 176 0.6092 0.6549
0.3174 101.7143 178 0.6022 0.6549
0.3309 102.8571 180 0.5928 0.6761
0.3309 104.0 182 0.6327 0.6408
0.3309 104.5714 183 0.6490 0.6338
0.3309 105.7143 185 0.6155 0.6479
0.3309 106.8571 187 0.6225 0.6620
0.3309 108.0 189 0.6732 0.6408
0.3124 108.5714 190 0.6808 0.6408
0.3124 109.7143 192 0.6585 0.6479
0.3124 110.8571 194 0.6122 0.6761
0.3124 112.0 196 0.6510 0.6549
0.3124 112.5714 197 0.7099 0.6408
0.3124 113.7143 199 0.7192 0.6338
0.3158 114.8571 201 0.6186 0.6901
0.3158 116.0 203 0.6071 0.7042
0.3158 116.5714 204 0.6419 0.6831
0.3158 117.7143 206 0.6679 0.6549
0.3158 118.8571 208 0.6825 0.6268
0.3026 120.0 210 0.6091 0.6972
0.3026 120.5714 211 0.5861 0.7394
0.3026 121.7143 213 0.6037 0.7113
0.3026 122.8571 215 0.6315 0.6761
0.3026 124.0 217 0.6328 0.6690
0.3026 124.5714 218 0.6187 0.6831
0.2968 125.7143 220 0.5843 0.7394
0.2968 126.8571 222 0.6126 0.7042
0.2968 128.0 224 0.6785 0.6549
0.2968 128.5714 225 0.6706 0.6479
0.2968 129.7143 227 0.6070 0.7113
0.2968 130.8571 229 0.5984 0.7254
0.294 132.0 231 0.6533 0.6620
0.294 132.5714 232 0.6802 0.6408
0.294 133.7143 234 0.6804 0.6408
0.294 134.8571 236 0.6228 0.7042
0.294 136.0 238 0.5849 0.7676
0.294 136.5714 239 0.5874 0.7676
0.3009 137.7143 241 0.6230 0.7042
0.3009 138.8571 243 0.6641 0.6549
0.3009 140.0 245 0.6435 0.6972
0.3009 140.5714 246 0.6134 0.7254
0.3009 141.7143 248 0.6063 0.7394
0.2873 142.8571 250 0.6347 0.6972
0.2873 144.0 252 0.6992 0.6690
0.2873 144.5714 253 0.7137 0.6408
0.2873 145.7143 255 0.6738 0.6690
0.2873 146.8571 257 0.6321 0.7113
0.2873 148.0 259 0.6135 0.7183
0.2821 148.5714 260 0.6195 0.7113
0.2821 149.7143 262 0.6544 0.6761
0.2821 150.8571 264 0.6464 0.6831
0.2821 152.0 266 0.6087 0.7324
0.2821 152.5714 267 0.6000 0.7394
0.2821 153.7143 269 0.6170 0.7113
0.3017 154.8571 271 0.6674 0.6831
0.3017 156.0 273 0.7137 0.6338
0.3017 156.5714 274 0.7014 0.6479
0.3017 157.7143 276 0.6091 0.7254
0.3017 158.8571 278 0.5626 0.7676
0.2857 160.0 280 0.5685 0.7606
0.2857 160.5714 281 0.5941 0.7113
0.2857 161.7143 283 0.6219 0.7113
0.2857 162.8571 285 0.6283 0.7113
0.2857 164.0 287 0.6314 0.7042
0.2857 164.5714 288 0.6369 0.6972
0.2819 165.7143 290 0.6446 0.6972
0.2819 166.8571 292 0.6541 0.6901
0.2819 168.0 294 0.6286 0.7183
0.2819 168.5714 295 0.6064 0.7183
0.2819 169.7143 297 0.5995 0.7254
0.2819 170.8571 299 0.6431 0.7254
0.2744 172.0 301 0.6797 0.6901
0.2744 172.5714 302 0.6716 0.6972
0.2744 173.7143 304 0.6510 0.7254
0.2744 174.8571 306 0.6362 0.7465
0.2744 176.0 308 0.6158 0.7606
0.2744 176.5714 309 0.6099 0.7676
0.2867 177.7143 311 0.6112 0.7535
0.2867 178.8571 313 0.6035 0.7465
0.2867 180.0 315 0.5816 0.7676
0.2867 180.5714 316 0.5818 0.7676
0.2867 181.7143 318 0.6078 0.7676
0.2883 182.8571 320 0.6083 0.7535
0.2883 184.0 322 0.5928 0.7465
0.2883 184.5714 323 0.5862 0.7535
0.2883 185.7143 325 0.5625 0.7676
0.2883 186.8571 327 0.5580 0.7817
0.2883 188.0 329 0.5945 0.7535
0.2852 188.5714 330 0.6321 0.6972
0.2852 189.7143 332 0.6650 0.6620
0.2852 190.8571 334 0.6612 0.6690
0.2852 192.0 336 0.6455 0.6761
0.2852 192.5714 337 0.6290 0.7113
0.2852 193.7143 339 0.6036 0.7394
0.2941 194.8571 341 0.5879 0.7535
0.2941 196.0 343 0.6135 0.7254
0.2941 196.5714 344 0.6295 0.7113
0.2941 197.7143 346 0.6445 0.6831
0.2941 198.8571 348 0.6591 0.6690
0.2692 200.0 350 0.6557 0.6831
0.2692 200.5714 351 0.6485 0.7113
0.2692 201.7143 353 0.6520 0.7183
0.2692 202.8571 355 0.6673 0.7113
0.2692 204.0 357 0.6814 0.7183
0.2692 204.5714 358 0.6694 0.7113
0.2666 205.7143 360 0.6350 0.7254
0.2666 206.8571 362 0.6091 0.7465
0.2666 208.0 364 0.6222 0.7394
0.2666 208.5714 365 0.6363 0.7394
0.2666 209.7143 367 0.6398 0.7394
0.2666 210.8571 369 0.6555 0.7254
0.2745 212.0 371 0.6555 0.7254
0.2745 212.5714 372 0.6467 0.7394
0.2745 213.7143 374 0.6216 0.7606
0.2745 214.8571 376 0.6066 0.7676
0.2745 216.0 378 0.6083 0.7606
0.2745 216.5714 379 0.6152 0.7535
0.2578 217.7143 381 0.6162 0.7535
0.2578 218.8571 383 0.6097 0.7535
0.2578 220.0 385 0.6003 0.7465
0.2578 220.5714 386 0.6064 0.7535
0.2578 221.7143 388 0.6182 0.7535
0.2637 222.8571 390 0.6465 0.7465
0.2637 224.0 392 0.6461 0.7535
0.2637 224.5714 393 0.6352 0.7535
0.2637 225.7143 395 0.6018 0.7606
0.2637 226.8571 397 0.5855 0.7746
0.2637 228.0 399 0.5916 0.7606
0.2696 228.5714 400 0.6031 0.7606
0.2696 229.7143 402 0.6308 0.7606
0.2696 230.8571 404 0.6435 0.7465
0.2696 232.0 406 0.6325 0.7465
0.2696 232.5714 407 0.6212 0.7535
0.2696 233.7143 409 0.5986 0.7535
0.2697 234.8571 411 0.5964 0.7465
0.2697 236.0 413 0.5950 0.7465
0.2697 236.5714 414 0.5986 0.7465
0.2697 237.7143 416 0.6066 0.7535
0.2697 238.8571 418 0.6035 0.7535
0.2659 240.0 420 0.6039 0.7535
0.2659 240.5714 421 0.6004 0.7535
0.2659 241.7143 423 0.6001 0.7535
0.2659 242.8571 425 0.5941 0.7465
0.2659 244.0 427 0.5942 0.7394
0.2659 244.5714 428 0.5972 0.7465
0.2529 245.7143 430 0.6077 0.7535
0.2529 246.8571 432 0.6173 0.7465
0.2529 248.0 434 0.6129 0.7606
0.2529 248.5714 435 0.6099 0.7606
0.2529 249.7143 437 0.6005 0.7606
0.2529 250.8571 439 0.5920 0.7606
0.261 252.0 441 0.5946 0.7606
0.261 252.5714 442 0.5992 0.7606
0.261 253.7143 444 0.6142 0.7606
0.261 254.8571 446 0.6289 0.7465
0.261 256.0 448 0.6316 0.7465
0.261 256.5714 449 0.6302 0.7535
0.2675 257.7143 451 0.6241 0.7535
0.2675 258.8571 453 0.6129 0.7535
0.2675 260.0 455 0.6066 0.7465
0.2675 260.5714 456 0.6061 0.7465
0.2675 261.7143 458 0.6098 0.7535
0.2737 262.8571 460 0.6172 0.7394
0.2737 264.0 462 0.6274 0.7324
0.2737 264.5714 463 0.6298 0.7324
0.2737 265.7143 465 0.6296 0.7324
0.2737 266.8571 467 0.6285 0.7324
0.2737 268.0 469 0.6265 0.7324
0.2504 268.5714 470 0.6274 0.7465
0.2504 269.7143 472 0.6286 0.7394
0.2504 270.8571 474 0.6236 0.7465
0.2504 272.0 476 0.6178 0.7465
0.2504 272.5714 477 0.6164 0.7465
0.2504 273.7143 479 0.6161 0.7465
0.2539 274.8571 481 0.6193 0.7465
0.2539 276.0 483 0.6236 0.7394
0.2539 276.5714 484 0.6258 0.7394
0.2539 277.7143 486 0.6308 0.7394
0.2539 278.8571 488 0.6349 0.7394
0.2508 280.0 490 0.6352 0.7394
0.2508 280.5714 491 0.6346 0.7394
0.2508 281.7143 493 0.6336 0.7394
0.2508 282.8571 495 0.6331 0.7394
0.2508 284.0 497 0.6324 0.7394
0.2508 284.5714 498 0.6319 0.7394
0.2393 285.7143 500 0.6316 0.7394

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.19.1