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Text Classification
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distilbert
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End of training

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  1. README.md +9 -29
  2. model.safetensors +1 -1
  3. runs/Mar22_00-03-48_2b329e9867ef/events.out.tfevents.1711065846.2b329e9867ef.177.6 +3 -0
  4. runs/Mar22_00-08-31_2b329e9867ef/events.out.tfevents.1711066151.2b329e9867ef.177.7 +3 -0
  5. runs/Mar22_00-18-24_2b329e9867ef/events.out.tfevents.1711066710.2b329e9867ef.177.8 +3 -0
  6. training_args.bin +2 -2
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7083
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- - Precision: 0.8225
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- - Recall: 0.8179
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- - F1: 0.8173
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- - Accuracy: 0.8179
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  ## Model description
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@@ -44,8 +44,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
@@ -55,28 +55,8 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 1.9419 | 0.14 | 30 | 1.8747 | 0.1996 | 0.1457 | 0.0783 | 0.1457 |
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- | 1.8097 | 0.27 | 60 | 1.6298 | 0.5707 | 0.5154 | 0.4893 | 0.5154 |
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- | 1.5214 | 0.41 | 90 | 1.3924 | 0.6685 | 0.5770 | 0.5477 | 0.5770 |
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- | 1.2785 | 0.54 | 120 | 1.1174 | 0.7150 | 0.6947 | 0.6917 | 0.6947 |
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- | 1.058 | 0.68 | 150 | 0.8779 | 0.7714 | 0.7451 | 0.7398 | 0.7451 |
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- | 0.8909 | 0.81 | 180 | 0.8686 | 0.7359 | 0.6863 | 0.6730 | 0.6863 |
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- | 0.795 | 0.95 | 210 | 0.7394 | 0.7970 | 0.7619 | 0.7541 | 0.7619 |
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- | 0.6453 | 1.08 | 240 | 0.6687 | 0.7733 | 0.7647 | 0.7620 | 0.7647 |
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- | 0.5226 | 1.22 | 270 | 0.6228 | 0.8175 | 0.8039 | 0.8036 | 0.8039 |
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- | 0.4012 | 1.35 | 300 | 0.6312 | 0.7818 | 0.7731 | 0.7726 | 0.7731 |
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- | 0.382 | 1.49 | 330 | 0.6198 | 0.7812 | 0.7759 | 0.7748 | 0.7759 |
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- | 0.4215 | 1.62 | 360 | 0.6579 | 0.7995 | 0.7899 | 0.7883 | 0.7899 |
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- | 0.3441 | 1.76 | 390 | 0.6891 | 0.7941 | 0.7871 | 0.7835 | 0.7871 |
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- | 0.2823 | 1.89 | 420 | 0.6695 | 0.8059 | 0.7983 | 0.7979 | 0.7983 |
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- | 0.2822 | 2.03 | 450 | 0.6461 | 0.7906 | 0.7871 | 0.7859 | 0.7871 |
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- | 0.1544 | 2.16 | 480 | 0.7253 | 0.7767 | 0.7759 | 0.7727 | 0.7759 |
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- | 0.1368 | 2.3 | 510 | 0.7756 | 0.7886 | 0.7843 | 0.7832 | 0.7843 |
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- | 0.1212 | 2.43 | 540 | 0.7391 | 0.7993 | 0.7955 | 0.7944 | 0.7955 |
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- | 0.2156 | 2.57 | 570 | 0.7008 | 0.8170 | 0.8123 | 0.8112 | 0.8123 |
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- | 0.1993 | 2.7 | 600 | 0.7077 | 0.8260 | 0.8207 | 0.8202 | 0.8207 |
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- | 0.0871 | 2.84 | 630 | 0.7046 | 0.8225 | 0.8179 | 0.8173 | 0.8179 |
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- | 0.1144 | 2.97 | 660 | 0.7082 | 0.8225 | 0.8179 | 0.8173 | 0.8179 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7301
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+ - Precision: 0.7889
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+ - Recall: 0.7759
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+ - F1: 0.7758
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+ - Accuracy: 0.7759
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.2611 | 1.07 | 30 | 0.7044 | 0.7874 | 0.7815 | 0.7813 | 0.7815 |
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+ | 0.1242 | 2.14 | 60 | 0.7301 | 0.7889 | 0.7759 | 0.7758 | 0.7759 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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