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RKessler
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VogagenRelation

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

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  1. README.md +19 -30
  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 [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2822
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- - Accuracy: 0.9345
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- - Precision: 0.9151
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- - Recall: 0.9579
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- - F1: 0.9360
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  ## Model description
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@@ -55,31 +55,20 @@ 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 | 0.21 | 100 | 0.6083 | 0.6973 | 0.6552 | 0.8331 | 0.7335 |
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- | No log | 0.42 | 200 | 0.4585 | 0.8097 | 0.7840 | 0.8549 | 0.8179 |
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- | No log | 0.62 | 300 | 0.3793 | 0.8627 | 0.8638 | 0.8612 | 0.8625 |
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- | No log | 0.83 | 400 | 0.3888 | 0.8612 | 0.8321 | 0.9048 | 0.8670 |
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- | 0.5367 | 1.04 | 500 | 0.3588 | 0.8705 | 0.8223 | 0.9454 | 0.8795 |
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- | 0.5367 | 1.25 | 600 | 0.5231 | 0.7956 | 0.7161 | 0.9797 | 0.8274 |
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- | 0.5367 | 1.46 | 700 | 0.3707 | 0.8736 | 0.8359 | 0.9298 | 0.8804 |
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- | 0.5367 | 1.66 | 800 | 0.2856 | 0.9119 | 0.9099 | 0.9142 | 0.9121 |
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- | 0.5367 | 1.87 | 900 | 0.2932 | 0.8947 | 0.9317 | 0.8518 | 0.8900 |
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- | 0.3695 | 2.08 | 1000 | 0.3262 | 0.9072 | 0.8979 | 0.9189 | 0.9082 |
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- | 0.3695 | 2.29 | 1100 | 0.3074 | 0.9041 | 0.8721 | 0.9470 | 0.9080 |
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- | 0.3695 | 2.49 | 1200 | 0.3233 | 0.9126 | 0.8773 | 0.9594 | 0.9165 |
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- | 0.3695 | 2.7 | 1300 | 0.3324 | 0.9103 | 0.8823 | 0.9470 | 0.9135 |
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- | 0.3695 | 2.91 | 1400 | 0.2775 | 0.9150 | 0.8947 | 0.9407 | 0.9171 |
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- | 0.2828 | 3.12 | 1500 | 0.2647 | 0.9243 | 0.9345 | 0.9126 | 0.9234 |
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- | 0.2828 | 3.33 | 1600 | 0.3034 | 0.9282 | 0.8984 | 0.9657 | 0.9308 |
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- | 0.2828 | 3.53 | 1700 | 0.3163 | 0.9282 | 0.9296 | 0.9267 | 0.9281 |
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- | 0.2828 | 3.74 | 1800 | 0.3032 | 0.9306 | 0.9095 | 0.9563 | 0.9323 |
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- | 0.2828 | 3.95 | 1900 | 0.3068 | 0.9321 | 0.9197 | 0.9470 | 0.9331 |
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- | 0.1867 | 4.16 | 2000 | 0.2762 | 0.9376 | 0.9269 | 0.9501 | 0.9384 |
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- | 0.1867 | 4.37 | 2100 | 0.2964 | 0.9360 | 0.9333 | 0.9392 | 0.9362 |
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- | 0.1867 | 4.57 | 2200 | 0.4208 | 0.9056 | 0.8591 | 0.9704 | 0.9114 |
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- | 0.1867 | 4.78 | 2300 | 0.3352 | 0.9314 | 0.9314 | 0.9314 | 0.9314 |
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- | 0.1867 | 4.99 | 2400 | 0.3005 | 0.9243 | 0.8977 | 0.9579 | 0.9268 |
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- | 0.145 | 5.2 | 2500 | 0.2822 | 0.9345 | 0.9151 | 0.9579 | 0.9360 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6962
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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 | 0.21 | 100 | 0.7035 | 0.4945 | 0.4972 | 0.9750 | 0.6586 |
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+ | No log | 0.42 | 200 | 0.6967 | 0.4852 | 0.4912 | 0.8253 | 0.6158 |
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+ | No log | 0.62 | 300 | 0.6965 | 0.4899 | 0.4880 | 0.4119 | 0.4467 |
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+ | No log | 0.83 | 400 | 0.6931 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6974 | 1.04 | 500 | 0.6959 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6974 | 1.25 | 600 | 0.7093 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6974 | 1.46 | 700 | 0.6949 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6974 | 1.66 | 800 | 0.6943 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6974 | 1.87 | 900 | 0.6947 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6965 | 2.08 | 1000 | 0.6932 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6965 | 2.29 | 1100 | 0.6948 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6965 | 2.49 | 1200 | 0.6934 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6965 | 2.7 | 1300 | 0.6934 | 0.5 | 0.5 | 1.0 | 0.6667 |
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+ | 0.6965 | 2.91 | 1400 | 0.6962 | 0.5 | 0.5 | 1.0 | 0.6667 |
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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