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RKessler
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EVALutionRelationTrain-5

Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +26 -18
  2. pytorch_model.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 [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6935
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  - Accuracy: 0.5
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- - Precision: 0.0
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- - Recall: 0.0
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- - F1: 0.0
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  ## Model description
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@@ -55,20 +55,28 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | No log | 0.35 | 100 | 0.7164 | 0.5 | 0.0 | 0.0 | 0.0 |
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- | No log | 0.71 | 200 | 0.7100 | 0.5 | 0.5 | 1.0 | 0.6667 |
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- | No log | 1.06 | 300 | 0.6935 | 0.5 | 0.5 | 1.0 | 0.6667 |
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- | No log | 1.42 | 400 | 0.6931 | 0.5 | 0.5 | 1.0 | 0.6667 |
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- | 0.7011 | 1.77 | 500 | 0.6957 | 0.5 | 0.0 | 0.0 | 0.0 |
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- | 0.7011 | 2.13 | 600 | 0.6950 | 0.5 | 0.0 | 0.0 | 0.0 |
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- | 0.7011 | 2.48 | 700 | 0.6989 | 0.5 | 0.5 | 1.0 | 0.6667 |
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- | 0.7011 | 2.84 | 800 | 0.6945 | 0.5 | 0.0 | 0.0 | 0.0 |
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- | 0.7011 | 3.19 | 900 | 0.6951 | 0.5 | 0.5 | 1.0 | 0.6667 |
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- | 0.6976 | 3.55 | 1000 | 0.6955 | 0.5 | 0.0 | 0.0 | 0.0 |
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- | 0.6976 | 3.9 | 1100 | 0.6958 | 0.5 | 0.0 | 0.0 | 0.0 |
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- | 0.6976 | 4.26 | 1200 | 0.6932 | 0.5 | 0.0 | 0.0 | 0.0 |
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- | 0.6976 | 4.61 | 1300 | 0.6938 | 0.5 | 0.5 | 1.0 | 0.6667 |
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- | 0.6976 | 4.96 | 1400 | 0.6935 | 0.5 | 0.0 | 0.0 | 0.0 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6933
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  - Accuracy: 0.5
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+ - Precision: 0.5
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+ - Recall: 1.0
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+ - F1: 0.6667
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 0.35 | 100 | 0.7119 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | No log | 0.71 | 200 | 0.7123 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | No log | 1.06 | 300 | 0.6936 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | No log | 1.42 | 400 | 0.6933 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6993 | 1.77 | 500 | 0.6945 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6993 | 2.13 | 600 | 0.6948 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6993 | 2.48 | 700 | 0.6999 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6993 | 2.84 | 800 | 0.6943 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6993 | 3.19 | 900 | 0.6951 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.698 | 3.55 | 1000 | 0.6945 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.698 | 3.9 | 1100 | 0.6956 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.698 | 4.26 | 1200 | 0.6933 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.698 | 4.61 | 1300 | 0.6941 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.698 | 4.96 | 1400 | 0.6934 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6964 | 5.32 | 1500 | 0.6933 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6964 | 5.67 | 1600 | 0.6943 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6964 | 6.03 | 1700 | 0.6946 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6964 | 6.38 | 1800 | 0.6932 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6964 | 6.74 | 1900 | 0.6952 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6952 | 7.09 | 2000 | 0.6934 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6952 | 7.45 | 2100 | 0.6935 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6952 | 7.8 | 2200 | 0.6933 | 0.5 | 0.5 | 1.0 | 0.6667 |
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  ### Framework versions
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