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distilbert-base-uncased-finetuned-ner

Token Classification
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distilbert
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  1. README.md +8 -8
  2. model.safetensors +1 -1
  3. runs/May14_23-28-09_PC-202201121646/events.out.tfevents.1715725712.PC-202201121646.2152.0 +2 -2
  4. runs/May14_23-28-09_PC-202201121646/events.out.tfevents.1715726328.PC-202201121646.2152.1 +3 -0
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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0632
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- - Precision: 0.9228
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- - Recall: 0.9347
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- - F1: 0.9287
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- - Accuracy: 0.9831
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  ## Model description
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@@ -55,9 +55,9 @@ 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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- | 0.2377 | 1.0 | 878 | 0.0710 | 0.9068 | 0.9172 | 0.9120 | 0.9802 |
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- | 0.0525 | 2.0 | 1756 | 0.0616 | 0.9213 | 0.9305 | 0.9259 | 0.9824 |
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- | 0.0304 | 3.0 | 2634 | 0.0632 | 0.9228 | 0.9347 | 0.9287 | 0.9831 |
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0622
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+ - Precision: 0.9250
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+ - Recall: 0.9367
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+ - F1: 0.9308
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+ - Accuracy: 0.9834
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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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+ | 0.2446 | 1.0 | 878 | 0.0727 | 0.8940 | 0.9136 | 0.9037 | 0.9786 |
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+ | 0.0514 | 2.0 | 1756 | 0.0604 | 0.9223 | 0.9331 | 0.9277 | 0.9829 |
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+ | 0.0312 | 3.0 | 2634 | 0.0622 | 0.9250 | 0.9367 | 0.9308 | 0.9834 |
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  ### Framework versions
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