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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 +35 -35
  2. model.safetensors +1 -1
  3. runs/Mar04_08-53-01_943307525f6c/events.out.tfevents.1709542394.943307525f6c.358.0 +3 -0
  4. runs/Mar04_08-53-01_943307525f6c/events.out.tfevents.1709542752.943307525f6c.358.1 +3 -0
  5. training_args.bin +1 -1
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: 0.5278
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- - Precision: 0.8182
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- - Recall: 0.6429
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- - F1: 0.7200
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- - Accuracy: 0.9074
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  ## Model description
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@@ -55,36 +55,36 @@ 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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- | No log | 1.0 | 6 | 0.8257 | 0.0 | 0.0 | 0.0 | 0.6667 |
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- | No log | 2.0 | 12 | 0.7596 | 0.0 | 0.0 | 0.0 | 0.6667 |
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- | No log | 3.0 | 18 | 0.6778 | 0.0 | 0.0 | 0.0 | 0.6667 |
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- | No log | 4.0 | 24 | 0.5430 | 0.5 | 0.1429 | 0.2222 | 0.7222 |
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- | No log | 5.0 | 30 | 0.4454 | 0.3333 | 0.2143 | 0.2609 | 0.7778 |
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- | No log | 6.0 | 36 | 0.4198 | 0.5 | 0.4286 | 0.4615 | 0.8333 |
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- | No log | 7.0 | 42 | 0.3951 | 0.5385 | 0.5 | 0.5185 | 0.8519 |
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- | No log | 8.0 | 48 | 0.4254 | 0.7 | 0.5 | 0.5833 | 0.8704 |
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- | No log | 9.0 | 54 | 0.4602 | 0.7 | 0.5 | 0.5833 | 0.8704 |
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- | No log | 10.0 | 60 | 0.4713 | 0.7 | 0.5 | 0.5833 | 0.8704 |
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- | No log | 11.0 | 66 | 0.4446 | 0.8 | 0.5714 | 0.6667 | 0.8889 |
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- | No log | 12.0 | 72 | 0.4407 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 13.0 | 78 | 0.4467 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 14.0 | 84 | 0.4571 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 15.0 | 90 | 0.4705 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 16.0 | 96 | 0.4844 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 17.0 | 102 | 0.4942 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 18.0 | 108 | 0.5010 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 19.0 | 114 | 0.5072 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 20.0 | 120 | 0.5111 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 21.0 | 126 | 0.5129 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 22.0 | 132 | 0.5158 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 23.0 | 138 | 0.5188 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 24.0 | 144 | 0.5211 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 25.0 | 150 | 0.5232 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 26.0 | 156 | 0.5251 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 27.0 | 162 | 0.5261 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 28.0 | 168 | 0.5268 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 29.0 | 174 | 0.5275 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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- | No log | 30.0 | 180 | 0.5278 | 0.8182 | 0.6429 | 0.7200 | 0.9074 |
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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: 0.5806
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+ - Precision: 0.8333
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+ - Recall: 0.4167
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+ - F1: 0.5556
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+ - Accuracy: 0.8621
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  ## Model description
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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 | 7 | 0.7508 | 0.0 | 0.0 | 0.0 | 0.7241 |
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+ | No log | 2.0 | 14 | 0.6957 | 0.0 | 0.0 | 0.0 | 0.7241 |
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+ | No log | 3.0 | 21 | 0.5574 | 0.0 | 0.0 | 0.0 | 0.7241 |
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+ | No log | 4.0 | 28 | 0.4661 | 0.0 | 0.0 | 0.0 | 0.7414 |
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+ | No log | 5.0 | 35 | 0.4346 | 0.2857 | 0.1667 | 0.2105 | 0.7931 |
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+ | No log | 6.0 | 42 | 0.3960 | 0.5714 | 0.3333 | 0.4211 | 0.8448 |
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+ | No log | 7.0 | 49 | 0.3890 | 0.5 | 0.3333 | 0.4 | 0.8621 |
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+ | No log | 8.0 | 56 | 0.4204 | 0.5714 | 0.3333 | 0.4211 | 0.8448 |
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+ | No log | 9.0 | 63 | 0.4701 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 10.0 | 70 | 0.5037 | 0.5714 | 0.3333 | 0.4211 | 0.8448 |
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+ | No log | 11.0 | 77 | 0.5123 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 12.0 | 84 | 0.5306 | 0.5714 | 0.3333 | 0.4211 | 0.8448 |
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+ | No log | 13.0 | 91 | 0.5420 | 0.5714 | 0.3333 | 0.4211 | 0.8448 |
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+ | No log | 14.0 | 98 | 0.5358 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 15.0 | 105 | 0.5314 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 16.0 | 112 | 0.5379 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 17.0 | 119 | 0.5487 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 18.0 | 126 | 0.5572 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 19.0 | 133 | 0.5629 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 20.0 | 140 | 0.5665 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 21.0 | 147 | 0.5691 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 22.0 | 154 | 0.5714 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 23.0 | 161 | 0.5733 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 24.0 | 168 | 0.5746 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 25.0 | 175 | 0.5759 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 26.0 | 182 | 0.5768 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 27.0 | 189 | 0.5786 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 28.0 | 196 | 0.5798 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 29.0 | 203 | 0.5804 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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+ | No log | 30.0 | 210 | 0.5806 | 0.8333 | 0.4167 | 0.5556 | 0.8621 |
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  ### Framework versions
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