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Aleksandar
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electra-srb-ner

Token Classification
Transformers
PyTorch
Safetensors
electra
Generated from Trainer
Inference Endpoints
Model card Files Community
1
Aleksandar commited on
Commit
401f554
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1 Parent(s): c2a5af3

add model

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Files changed (3) hide show
  1. README.md +11 -17
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,7 +17,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.9509610737256943
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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
@@ -27,11 +27,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2686
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- - Precision: 0.8132
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- - Recall: 0.7889
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- - F1: 0.8009
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- - Accuracy: 0.9510
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  ## Model description
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@@ -56,22 +56,16 @@ 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 | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 207 | 0.2887 | 0.7392 | 0.6269 | 0.6784 | 0.9221 |
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- | No log | 2.0 | 414 | 0.2076 | 0.7690 | 0.7147 | 0.7409 | 0.9397 |
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- | 0.2949 | 3.0 | 621 | 0.2011 | 0.7698 | 0.7583 | 0.7640 | 0.9441 |
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- | 0.2949 | 4.0 | 828 | 0.2077 | 0.7600 | 0.7807 | 0.7702 | 0.9451 |
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- | 0.089 | 5.0 | 1035 | 0.2198 | 0.7884 | 0.7684 | 0.7783 | 0.9465 |
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- | 0.089 | 6.0 | 1242 | 0.2437 | 0.7885 | 0.7824 | 0.7854 | 0.9474 |
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- | 0.089 | 7.0 | 1449 | 0.2394 | 0.7986 | 0.7970 | 0.7978 | 0.9511 |
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- | 0.0322 | 8.0 | 1656 | 0.2675 | 0.8135 | 0.7775 | 0.7951 | 0.9497 |
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- | 0.0322 | 9.0 | 1863 | 0.2832 | 0.8161 | 0.7798 | 0.7975 | 0.9508 |
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- | 0.0141 | 10.0 | 2070 | 0.2686 | 0.8132 | 0.7889 | 0.8009 | 0.9510 |
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  ### Framework versions
 
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  metric:
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  name: Accuracy
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  type: accuracy
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+ value: 0.9418150723128973
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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 was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2062
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+ - Precision: 0.7553
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+ - Recall: 0.7362
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+ - F1: 0.7456
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+ - Accuracy: 0.9418
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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: 4
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  ### Training results
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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 | 207 | 0.2894 | 0.7278 | 0.6252 | 0.6726 | 0.9207 |
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+ | No log | 2.0 | 414 | 0.2175 | 0.7463 | 0.6984 | 0.7216 | 0.9352 |
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+ | 0.3035 | 3.0 | 621 | 0.2189 | 0.7826 | 0.7049 | 0.7417 | 0.9398 |
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+ | 0.3035 | 4.0 | 828 | 0.2062 | 0.7553 | 0.7362 | 0.7456 | 0.9418 |
 
 
 
 
 
 
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  ### Framework versions
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