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AlvianKhairi
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Scicite_classification_model

Text Classification
Transformers
PyTorch
bert
generated_from_trainer
Eval Results
Inference Endpoints
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End of training

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  1. README.md +13 -15
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8493449781659389
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the scicite dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2264
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- - Accuracy: 0.8493
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  ## Model description
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@@ -57,27 +57,25 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.3988 | 1.0 | 513 | 0.4386 | 0.8428 |
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- | 0.2701 | 2.0 | 1026 | 0.5087 | 0.8504 |
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- | 0.1789 | 3.0 | 1539 | 0.6278 | 0.8526 |
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- | 0.1047 | 4.0 | 2052 | 0.8142 | 0.8548 |
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- | 0.0653 | 5.0 | 2565 | 1.0136 | 0.8461 |
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- | 0.0376 | 6.0 | 3078 | 1.1257 | 0.8417 |
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- | 0.0237 | 7.0 | 3591 | 1.1632 | 0.8341 |
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- | 0.0135 | 8.0 | 4104 | 1.2346 | 0.8493 |
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- | 0.0124 | 9.0 | 4617 | 1.2027 | 0.8483 |
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- | 0.0059 | 10.0 | 5130 | 1.2264 | 0.8493 |
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  ### Framework versions
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- - Transformers 4.33.2
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.5
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  - Tokenizers 0.13.3
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9224890829694323
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the scicite dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4704
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+ - Accuracy: 0.9225
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 8
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.2493 | 1.0 | 513 | 0.2034 | 0.9214 |
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+ | 0.1777 | 2.0 | 1026 | 0.1942 | 0.9247 |
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+ | 0.1385 | 3.0 | 1539 | 0.2552 | 0.9247 |
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+ | 0.1019 | 4.0 | 2052 | 0.2995 | 0.9258 |
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+ | 0.0705 | 5.0 | 2565 | 0.3964 | 0.9181 |
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+ | 0.0444 | 6.0 | 3078 | 0.4243 | 0.9203 |
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+ | 0.0331 | 7.0 | 3591 | 0.4904 | 0.9192 |
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+ | 0.0223 | 8.0 | 4104 | 0.4704 | 0.9225 |
 
 
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  ### Framework versions
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+ - Transformers 4.33.3
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.5
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  - Tokenizers 0.13.3
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