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ekolasky
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longformer_result_detection

Token Classification
Transformers
PyTorch
longformer
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +15 -15
  2. pytorch_model.bin +1 -1
  3. 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 [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1156
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- - Precision: 0.6277
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- - Recall: 0.6694
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- - F1: 0.6479
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- - Accuracy: 0.9802
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  ## Model description
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@@ -55,16 +55,16 @@ 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 | 348 | 0.0716 | 0.4966 | 0.6050 | 0.5455 | 0.9740 |
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- | 0.1189 | 2.0 | 696 | 0.0634 | 0.5302 | 0.6195 | 0.5714 | 0.9770 |
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- | 0.0588 | 3.0 | 1044 | 0.0760 | 0.5518 | 0.6424 | 0.5937 | 0.9774 |
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- | 0.0588 | 4.0 | 1392 | 0.0760 | 0.6121 | 0.6528 | 0.6318 | 0.9785 |
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- | 0.0282 | 5.0 | 1740 | 0.0910 | 0.6107 | 0.6424 | 0.6261 | 0.9792 |
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- | 0.0167 | 6.0 | 2088 | 0.1372 | 0.6 | 0.5364 | 0.5664 | 0.9745 |
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- | 0.0167 | 7.0 | 2436 | 0.1144 | 0.6028 | 0.6216 | 0.6121 | 0.9793 |
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- | 0.0087 | 8.0 | 2784 | 0.1011 | 0.6120 | 0.6590 | 0.6346 | 0.9805 |
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- | 0.0061 | 9.0 | 3132 | 0.1239 | 0.6315 | 0.6341 | 0.6328 | 0.9802 |
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- | 0.0061 | 10.0 | 3480 | 0.1156 | 0.6277 | 0.6694 | 0.6479 | 0.9802 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1283
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+ - Precision: 0.6234
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+ - Recall: 0.6881
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+ - F1: 0.6542
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+ - Accuracy: 0.9798
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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 | 348 | 0.0640 | 0.5015 | 0.6923 | 0.5817 | 0.9751 |
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+ | 0.1163 | 2.0 | 696 | 0.0599 | 0.5470 | 0.6528 | 0.5953 | 0.9774 |
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+ | 0.0516 | 3.0 | 1044 | 0.0666 | 0.5941 | 0.7089 | 0.6464 | 0.9797 |
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+ | 0.0516 | 4.0 | 1392 | 0.0753 | 0.6 | 0.7173 | 0.6534 | 0.9797 |
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+ | 0.0231 | 5.0 | 1740 | 0.0920 | 0.6015 | 0.6840 | 0.6401 | 0.9791 |
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+ | 0.0131 | 6.0 | 2088 | 0.1148 | 0.6201 | 0.6549 | 0.6370 | 0.9790 |
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+ | 0.0131 | 7.0 | 2436 | 0.1112 | 0.6082 | 0.7422 | 0.6685 | 0.9800 |
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+ | 0.0078 | 8.0 | 2784 | 0.1204 | 0.6099 | 0.6923 | 0.6485 | 0.9797 |
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+ | 0.0043 | 9.0 | 3132 | 0.1307 | 0.6128 | 0.6549 | 0.6332 | 0.9794 |
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+ | 0.0043 | 10.0 | 3480 | 0.1283 | 0.6234 | 0.6881 | 0.6542 | 0.9798 |
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  ### Framework versions
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