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distilhubert-finetuned-mixed-data

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  1. README.md +12 -22
  2. checkpoint-24/config.json +4 -4
  3. checkpoint-24/model.safetensors +1 -1
  4. checkpoint-24/optimizer.pt +1 -1
  5. checkpoint-24/scheduler.pt +1 -1
  6. checkpoint-24/trainer_state.json +10 -10
  7. checkpoint-24/training_args.bin +1 -1
  8. checkpoint-48/config.json +4 -4
  9. checkpoint-48/model.safetensors +1 -1
  10. checkpoint-48/optimizer.pt +1 -1
  11. checkpoint-48/scheduler.pt +1 -1
  12. checkpoint-48/trainer_state.json +18 -18
  13. checkpoint-48/training_args.bin +1 -1
  14. checkpoint-72/config.json +4 -4
  15. checkpoint-72/model.safetensors +1 -1
  16. checkpoint-72/optimizer.pt +1 -1
  17. checkpoint-72/scheduler.pt +1 -1
  18. checkpoint-72/trainer_state.json +26 -26
  19. checkpoint-72/training_args.bin +1 -1
  20. checkpoint-97/config.json +4 -4
  21. checkpoint-97/model.safetensors +1 -1
  22. checkpoint-97/optimizer.pt +1 -1
  23. checkpoint-97/scheduler.pt +1 -1
  24. checkpoint-97/trainer_state.json +35 -35
  25. checkpoint-97/training_args.bin +1 -1
  26. config.json +4 -4
  27. model.safetensors +1 -1
  28. runs/Sep10_13-50-27_ubumarcos/events.out.tfevents.1725969028.ubumarcos +3 -0
  29. runs/Sep10_17-06-13_ubumarcos/events.out.tfevents.1725980774.ubumarcos +3 -0
  30. runs/Sep10_18-38-16_ubumarcos/events.out.tfevents.1725986297.ubumarcos +3 -0
  31. training_args.bin +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
21
 
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4448
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- - Accuracy: 0.8553
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- - Precision: 0.8527
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- - Recall: 0.8553
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- - F1: 0.8522
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  ## Model description
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@@ -44,7 +44,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0001
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 123
@@ -57,22 +57,12 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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- |:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | No log | 0.9897 | 24 | 1.3056 | 0.4341 | 0.1885 | 0.4341 | 0.2628 |
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- | No log | 1.9794 | 48 | 1.1732 | 0.4341 | 0.1885 | 0.4341 | 0.2628 |
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- | No log | 2.9691 | 72 | 0.9256 | 0.6357 | 0.6651 | 0.6357 | 0.5935 |
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- | No log | 4.0 | 97 | 0.7872 | 0.6563 | 0.6724 | 0.6563 | 0.6387 |
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- | No log | 4.9897 | 121 | 0.6242 | 0.7597 | 0.7615 | 0.7597 | 0.7448 |
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- | No log | 5.9794 | 145 | 0.5990 | 0.7726 | 0.8035 | 0.7726 | 0.7744 |
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- | No log | 6.9691 | 169 | 0.5286 | 0.7907 | 0.8075 | 0.7907 | 0.7889 |
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- | No log | 8.0 | 194 | 0.4616 | 0.8140 | 0.8345 | 0.8140 | 0.8191 |
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- | No log | 8.9897 | 218 | 0.5001 | 0.8114 | 0.8142 | 0.8114 | 0.8021 |
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- | No log | 9.9794 | 242 | 0.4530 | 0.8165 | 0.8131 | 0.8165 | 0.8126 |
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- | No log | 10.9691 | 266 | 0.4203 | 0.8553 | 0.8586 | 0.8553 | 0.8544 |
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- | No log | 12.0 | 291 | 0.4621 | 0.8450 | 0.8423 | 0.8450 | 0.8402 |
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- | No log | 12.9897 | 315 | 0.4583 | 0.8501 | 0.8493 | 0.8501 | 0.8471 |
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- | No log | 13.9794 | 339 | 0.4448 | 0.8553 | 0.8527 | 0.8553 | 0.8522 |
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  ### Framework versions
 
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22
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on an unknown dataset.
23
  It achieves the following results on the evaluation set:
24
+ - Loss: 0.5203
25
+ - Accuracy: 0.7881
26
+ - Precision: 0.7937
27
+ - Recall: 0.7881
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+ - F1: 0.7617
29
 
30
  ## Model description
31
 
 
44
  ### Training hyperparameters
45
 
46
  The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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  - train_batch_size: 8
49
  - eval_batch_size: 8
50
  - seed: 123
 
57
 
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  ### Training results
59
 
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 0.9897 | 24 | 1.2071 | 0.4935 | 0.2436 | 0.4935 | 0.3262 |
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+ | No log | 1.9794 | 48 | 0.9013 | 0.6718 | 0.7410 | 0.6718 | 0.6040 |
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+ | No log | 2.9691 | 72 | 0.6878 | 0.7235 | 0.7739 | 0.7235 | 0.6509 |
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+ | No log | 4.0 | 97 | 0.5203 | 0.7881 | 0.7937 | 0.7881 | 0.7617 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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