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vit-Facial-Expression-Recognition

Image Classification
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vit
Generated from Trainer
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  1. README.md +15 -63
  2. all_results.json +6 -6
  3. eval_results.json +6 -6
  4. model.safetensors +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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  library_name: transformers
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- base_model: motheecreator/vit-Facial-Expression-Recognition
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # vit-Facial-Expression-Recognition
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- This model is a fine-tuned version of [motheecreator/vit-Facial-Expression-Recognition](https://huggingface.co/motheecreator/vit-Facial-Expression-Recognition) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5019
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- - Accuracy: 0.8341
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  ## Model description
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@@ -52,65 +52,17 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 1.2888 | 0.1686 | 100 | 1.2016 | 0.6816 |
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- | 1.0357 | 0.3373 | 200 | 0.9279 | 0.6733 |
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- | 0.9495 | 0.5059 | 300 | 0.8319 | 0.6941 |
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- | 0.891 | 0.6745 | 400 | 0.7351 | 0.7359 |
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- | 0.8208 | 0.8432 | 500 | 0.6590 | 0.7651 |
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- | 0.7907 | 1.0118 | 600 | 0.6199 | 0.7847 |
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- | 0.7374 | 1.1804 | 700 | 0.5943 | 0.7950 |
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- | 0.7456 | 1.3491 | 800 | 0.5860 | 0.7969 |
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- | 0.7229 | 1.5177 | 900 | 0.5749 | 0.8018 |
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- | 0.699 | 1.6863 | 1000 | 0.5556 | 0.8076 |
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- | 0.7025 | 1.8550 | 1100 | 0.5585 | 0.8070 |
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- | 0.6871 | 2.0236 | 1200 | 0.5359 | 0.8150 |
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- | 0.6427 | 2.1922 | 1300 | 0.5455 | 0.8107 |
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- | 0.6499 | 2.3609 | 1400 | 0.5604 | 0.8059 |
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- | 0.6416 | 2.5295 | 1500 | 0.5347 | 0.8153 |
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- | 0.6404 | 2.6981 | 1600 | 0.5252 | 0.8191 |
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- | 0.6438 | 2.8668 | 1700 | 0.5345 | 0.8150 |
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- | 0.6168 | 3.0354 | 1800 | 0.5313 | 0.8178 |
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- | 0.5886 | 3.2040 | 1900 | 0.5199 | 0.8212 |
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- | 0.5915 | 3.3727 | 2000 | 0.5276 | 0.8195 |
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- | 0.5862 | 3.5413 | 2100 | 0.5163 | 0.8229 |
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- | 0.5649 | 3.7099 | 2200 | 0.5094 | 0.8251 |
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- | 0.5705 | 3.8786 | 2300 | 0.5099 | 0.8243 |
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- | 0.5393 | 4.0472 | 2400 | 0.5095 | 0.8240 |
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- | 0.5061 | 4.2159 | 2500 | 0.5219 | 0.8228 |
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- | 0.5019 | 4.3845 | 2600 | 0.5114 | 0.8255 |
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- | 0.5104 | 4.5531 | 2700 | 0.5010 | 0.8270 |
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- | 0.4951 | 4.7218 | 2800 | 0.4996 | 0.8283 |
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- | 0.4964 | 4.8904 | 2900 | 0.4961 | 0.8298 |
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- | 0.4694 | 5.0590 | 3000 | 0.4980 | 0.8302 |
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- | 0.461 | 5.2277 | 3100 | 0.5042 | 0.8276 |
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- | 0.4347 | 5.3963 | 3200 | 0.4990 | 0.8297 |
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- | 0.447 | 5.5649 | 3300 | 0.5037 | 0.8268 |
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- | 0.4406 | 5.7336 | 3400 | 0.4956 | 0.8310 |
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- | 0.4411 | 5.9022 | 3500 | 0.4977 | 0.8307 |
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- | 0.3996 | 6.0708 | 3600 | 0.5017 | 0.8313 |
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- | 0.3969 | 6.2395 | 3700 | 0.5056 | 0.8314 |
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- | 0.3869 | 6.4081 | 3800 | 0.5034 | 0.8304 |
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- | 0.3916 | 6.5767 | 3900 | 0.5084 | 0.8302 |
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- | 0.3975 | 6.7454 | 4000 | 0.5060 | 0.8308 |
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- | 0.3924 | 6.9140 | 4100 | 0.4981 | 0.8326 |
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- | 0.3494 | 7.0826 | 4200 | 0.5055 | 0.8296 |
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- | 0.3447 | 7.2513 | 4300 | 0.5048 | 0.8326 |
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- | 0.3513 | 7.4199 | 4400 | 0.5052 | 0.8306 |
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- | 0.3539 | 7.5885 | 4500 | 0.5019 | 0.8341 |
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- | 0.3511 | 7.7572 | 4600 | 0.4999 | 0.8329 |
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- | 0.3546 | 7.9258 | 4700 | 0.5003 | 0.8328 |
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- | 0.3292 | 8.0944 | 4800 | 0.5032 | 0.8325 |
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- | 0.3229 | 8.2631 | 4900 | 0.5023 | 0.8327 |
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- | 0.326 | 8.4317 | 5000 | 0.5031 | 0.8321 |
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- | 0.3243 | 8.6003 | 5100 | 0.5044 | 0.8332 |
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- | 0.3243 | 8.7690 | 5200 | 0.5012 | 0.8332 |
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- | 0.3231 | 8.9376 | 5300 | 0.5013 | 0.8332 |
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- | 0.316 | 9.1062 | 5400 | 0.5019 | 0.8331 |
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- | 0.3264 | 9.2749 | 5500 | 0.5015 | 0.8331 |
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- | 0.306 | 9.4435 | 5600 | 0.5020 | 0.8327 |
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- | 0.3143 | 9.6121 | 5700 | 0.5018 | 0.8330 |
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- | 0.3061 | 9.7808 | 5800 | 0.5014 | 0.8335 |
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- | 0.3131 | 9.9494 | 5900 | 0.5014 | 0.8334 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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+ base_model: carlosleao/vit-Facial-Expression-Recognition
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # vit-Facial-Expression-Recognition
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+ This model is a fine-tuned version of [carlosleao/vit-Facial-Expression-Recognition](https://huggingface.co/carlosleao/vit-Facial-Expression-Recognition) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6115
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+ - Accuracy: 0.3764
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 1.7238 | 0.8959 | 100 | 1.6509 | 0.3764 |
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+ | 1.6152 | 1.7917 | 200 | 1.6163 | 0.3764 |
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+ | 1.6076 | 2.6876 | 300 | 1.6110 | 0.3764 |
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+ | 1.6158 | 3.5834 | 400 | 1.6094 | 0.3764 |
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+ | 1.6031 | 4.4793 | 500 | 1.6115 | 0.3764 |
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+ | 1.604 | 5.3751 | 600 | 1.6105 | 0.3764 |
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+ | 1.6087 | 6.2710 | 700 | 1.6087 | 0.3764 |
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+ | 1.5989 | 7.1669 | 800 | 1.6103 | 0.3764 |
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+ | 1.606 | 8.0627 | 900 | 1.6085 | 0.3764 |
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+ | 1.6013 | 8.9586 | 1000 | 1.6085 | 0.3764 |
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+ | 1.6066 | 9.8544 | 1100 | 1.6084 | 0.3764 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
all_results.json CHANGED
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  {
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- "epoch": 10.0,
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- "eval_accuracy": 0.8340624011805629,
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- "eval_loss": 0.5018735527992249,
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- "eval_runtime": 108.9933,
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- "eval_samples_per_second": 348.168,
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- "eval_steps_per_second": 10.881
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  }
 
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  {
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+ "epoch": 9.944008958566629,
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+ "eval_accuracy": 0.3763621123218776,
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+ "eval_loss": 1.6114516258239746,
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+ "eval_runtime": 6.6377,
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+ "eval_samples_per_second": 539.194,
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+ "eval_steps_per_second": 16.873
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  }
eval_results.json CHANGED
@@ -1,8 +1,8 @@
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  {
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- "epoch": 10.0,
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- "eval_accuracy": 0.8340624011805629,
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- "eval_loss": 0.5018735527992249,
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- "eval_runtime": 108.9933,
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- "eval_samples_per_second": 348.168,
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- "eval_steps_per_second": 10.881
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  }
 
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  {
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+ "epoch": 9.944008958566629,
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+ "eval_accuracy": 0.3763621123218776,
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+ "eval_loss": 1.6114516258239746,
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+ "eval_runtime": 6.6377,
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+ "eval_samples_per_second": 539.194,
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+ "eval_steps_per_second": 16.873
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  }
model.safetensors CHANGED
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