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distilbert_finetune_own_data_model

Token Classification
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distilbert
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End of training

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  1. README.md +36 -56
  2. model.safetensors +1 -1
  3. runs/Mar02_12-11-58_de05560c5ef4/events.out.tfevents.1709381532.de05560c5ef4.888.4 +3 -0
  4. runs/Mar02_12-11-58_de05560c5ef4/events.out.tfevents.1709381542.de05560c5ef4.888.5 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,7 +20,7 @@ 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: 0.0004
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  - Precision: 1.0
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  - Recall: 1.0
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  - F1: 1.0
@@ -44,67 +44,47 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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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- - num_epochs: 50
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 3 | 0.5698 | 0.0 | 0.0 | 0.0 | 0.68 |
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- | No log | 2.0 | 6 | 0.4859 | 0.0 | 0.0 | 0.0 | 0.68 |
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- | No log | 3.0 | 9 | 0.3988 | 1.0 | 0.2 | 0.3333 | 0.8 |
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- | No log | 4.0 | 12 | 0.3074 | 1.0 | 0.6 | 0.7500 | 0.92 |
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- | No log | 5.0 | 15 | 0.2169 | 1.0 | 0.8 | 0.8889 | 0.96 |
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- | No log | 6.0 | 18 | 0.1405 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 7.0 | 21 | 0.0844 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 8.0 | 24 | 0.0445 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 9.0 | 27 | 0.0221 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 10.0 | 30 | 0.0113 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 11.0 | 33 | 0.0062 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 12.0 | 36 | 0.0038 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 13.0 | 39 | 0.0025 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 14.0 | 42 | 0.0019 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 15.0 | 45 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 16.0 | 48 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 17.0 | 51 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 18.0 | 54 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 19.0 | 57 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 20.0 | 60 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 21.0 | 63 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 22.0 | 66 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 23.0 | 69 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 24.0 | 72 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 25.0 | 75 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 26.0 | 78 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 27.0 | 81 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 28.0 | 84 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 29.0 | 87 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 30.0 | 90 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 31.0 | 93 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 32.0 | 96 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 33.0 | 99 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 34.0 | 102 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 35.0 | 105 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 36.0 | 108 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 37.0 | 111 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 38.0 | 114 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 39.0 | 117 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 40.0 | 120 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 41.0 | 123 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 42.0 | 126 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 43.0 | 129 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 44.0 | 132 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 45.0 | 135 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 46.0 | 138 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 47.0 | 141 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 48.0 | 144 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 49.0 | 147 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 50.0 | 150 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
 
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21
  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: 0.0000
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  - Precision: 1.0
25
  - Recall: 1.0
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  - F1: 1.0
 
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
49
  - seed: 42
50
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 30
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
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+ | No log | 1.0 | 5 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 2.0 | 10 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 3.0 | 15 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 4.0 | 20 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 5.0 | 25 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 6.0 | 30 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 7.0 | 35 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 8.0 | 40 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 9.0 | 45 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 10.0 | 50 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 11.0 | 55 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 12.0 | 60 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 13.0 | 65 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 14.0 | 70 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 15.0 | 75 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 16.0 | 80 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 17.0 | 85 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 18.0 | 90 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 19.0 | 95 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 20.0 | 100 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 21.0 | 105 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 22.0 | 110 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 23.0 | 115 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 24.0 | 120 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 25.0 | 125 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 26.0 | 130 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 27.0 | 135 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 28.0 | 140 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 29.0 | 145 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 30.0 | 150 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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