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distilbert-base-uncased-finetuned-ner

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distilbert
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  1. README.md +9 -9
  2. model.safetensors +1 -1
  3. runs/May14_13-35-24_PC-202201121646/events.out.tfevents.1715690151.PC-202201121646.21440.0 +2 -2
  4. runs/May14_13-35-24_PC-202201121646/events.out.tfevents.1715690767.PC-202201121646.21440.1 +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: 0.0622
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- - Precision: 0.9251
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- - Recall: 0.9363
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- - F1: 0.9307
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- - Accuracy: 0.9836
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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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- | 0.2518 | 1.0 | 878 | 0.0703 | 0.9007 | 0.9205 | 0.9105 | 0.9802 |
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- | 0.0527 | 2.0 | 1756 | 0.0605 | 0.9219 | 0.9335 | 0.9277 | 0.9830 |
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- | 0.0303 | 3.0 | 2634 | 0.0622 | 0.9251 | 0.9363 | 0.9307 | 0.9836 |
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  ### Framework versions
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  - Transformers 4.39.3
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- - Pytorch 2.2.2+cpu
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  - Datasets 2.19.1
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  - Tokenizers 0.15.2
 
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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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  | 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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  - Transformers 4.39.3
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+ - Pytorch 2.2.0+cu118
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  - Datasets 2.19.1
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  - Tokenizers 0.15.2
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