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bert-tiny-finetuned-ner

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  1. README.md +15 -13
  2. pytorch_model.bin +1 -1
  3. runs/Sep01_23-31-04_c5dc93782852/1630539088.1161077/events.out.tfevents.1630539088.c5dc93782852.76.1 +3 -0
  4. runs/Sep01_23-31-04_c5dc93782852/events.out.tfevents.1630539088.c5dc93782852.76.0 +3 -0
  5. runs/Sep01_23-47-50_c5dc93782852/1630540075.4173546/events.out.tfevents.1630540075.c5dc93782852.76.3 +3 -0
  6. runs/Sep01_23-47-50_c5dc93782852/events.out.tfevents.1630540075.c5dc93782852.76.2 +3 -0
  7. runs/Sep01_23-48-13_c5dc93782852/1630540097.9292622/events.out.tfevents.1630540097.c5dc93782852.76.5 +3 -0
  8. runs/Sep01_23-48-13_c5dc93782852/events.out.tfevents.1630540097.c5dc93782852.76.4 +3 -0
  9. runs/Sep01_23-48-13_c5dc93782852/events.out.tfevents.1630540235.c5dc93782852.76.6 +3 -0
  10. training_args.bin +1 -1
README.md CHANGED
@@ -21,16 +21,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.5147295742232451
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  - name: Recall
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  type: recall
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- value: 0.5003915426781519
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  - name: F1
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  type: f1
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- value: 0.5074593000170173
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  - name: Accuracy
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  type: accuracy
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- value: 0.8967226396810015
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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
@@ -40,11 +40,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4053
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- - Precision: 0.5147
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- - Recall: 0.5004
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- - F1: 0.5075
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- - Accuracy: 0.8967
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  ## Model description
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@@ -69,15 +69,17 @@ 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: 3
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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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- | 0.9306 | 1.0 | 878 | 0.5040 | 0.4321 | 0.4099 | 0.4207 | 0.8762 |
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- | 0.4777 | 2.0 | 1756 | 0.4240 | 0.4978 | 0.4851 | 0.4913 | 0.8926 |
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- | 0.4306 | 3.0 | 2634 | 0.4053 | 0.5147 | 0.5004 | 0.5075 | 0.8967 |
 
 
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  ### Framework versions
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.8083060109289617
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  - name: Recall
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  type: recall
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+ value: 0.8273856136033113
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  - name: F1
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  type: f1
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+ value: 0.8177345348001547
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9597597979252387
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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 [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1689
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+ - Precision: 0.8083
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+ - Recall: 0.8274
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+ - F1: 0.8177
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+ - Accuracy: 0.9598
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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: 5
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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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+ | 0.0355 | 1.0 | 878 | 0.1692 | 0.8072 | 0.8248 | 0.8159 | 0.9594 |
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+ | 0.0411 | 2.0 | 1756 | 0.1678 | 0.8101 | 0.8277 | 0.8188 | 0.9600 |
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+ | 0.0386 | 3.0 | 2634 | 0.1697 | 0.8103 | 0.8269 | 0.8186 | 0.9599 |
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+ | 0.0373 | 4.0 | 3512 | 0.1694 | 0.8106 | 0.8263 | 0.8183 | 0.9600 |
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+ | 0.0383 | 5.0 | 4390 | 0.1689 | 0.8083 | 0.8274 | 0.8177 | 0.9598 |
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  ### Framework versions
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