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ramybaly
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ner_nerd_fine

Token Classification
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PyTorch
TensorBoard
bert
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ramybaly commited on
Commit
1677520
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1 Parent(s): 6548d2d

add model

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Files changed (6) hide show
  1. README.md +17 -12
  2. pytorch_model.bin +1 -1
  3. runs/Aug20_12-20-27_ip-172-31-23-147/1629462041.0933988/events.out.tfevents.1629462041.ip-172-31-23-147.8390.1 +3 -0
  4. runs/Aug20_12-20-27_ip-172-31-23-147/events.out.tfevents.1629462041.ip-172-31-23-147.8390.0 +3 -0
  5. runs/Aug20_12-20-27_ip-172-31-23-147/events.out.tfevents.1629471031.ip-172-31-23-147.8390.2 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.9077183979155076
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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
@@ -32,11 +32,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the nerd dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3494
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- - Precision: 0.6327
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- - Recall: 0.6793
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- - F1: 0.6551
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- - Accuracy: 0.9077
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  ## Model description
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@@ -62,17 +62,22 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.1
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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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- | 0.548 | 1.0 | 8235 | 0.3281 | 0.6101 | 0.6630 | 0.6355 | 0.9029 |
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- | 0.2857 | 2.0 | 16470 | 0.3139 | 0.6355 | 0.6706 | 0.6526 | 0.9073 |
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- | 0.2183 | 3.0 | 24705 | 0.3294 | 0.6374 | 0.6788 | 0.6575 | 0.9082 |
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- | 0.1658 | 4.0 | 32940 | 0.3440 | 0.6366 | 0.6815 | 0.6583 | 0.9087 |
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- | 0.1286 | 5.0 | 41175 | 0.3702 | 0.6364 | 0.6812 | 0.6580 | 0.9081 |
 
 
 
 
 
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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: 0.9058961278375514
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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 [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the nerd dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5332
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+ - Precision: 0.6337
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+ - Recall: 0.6731
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+ - F1: 0.6528
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+ - Accuracy: 0.9059
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  ## Model description
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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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  - lr_scheduler_warmup_ratio: 0.1
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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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+ | 0.6337 | 1.0 | 8235 | 0.3391 | 0.5974 | 0.6567 | 0.6256 | 0.9010 |
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+ | 0.3086 | 2.0 | 16470 | 0.3188 | 0.6276 | 0.6607 | 0.6437 | 0.9061 |
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+ | 0.2394 | 3.0 | 24705 | 0.3304 | 0.6284 | 0.6740 | 0.6504 | 0.9064 |
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+ | 0.1841 | 4.0 | 32940 | 0.3451 | 0.6286 | 0.6749 | 0.6509 | 0.9065 |
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+ | 0.1392 | 5.0 | 41175 | 0.3837 | 0.6251 | 0.6745 | 0.6489 | 0.9056 |
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+ | 0.1056 | 6.0 | 49410 | 0.4185 | 0.6307 | 0.6751 | 0.6521 | 0.9057 |
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+ | 0.0812 | 7.0 | 57645 | 0.4615 | 0.6288 | 0.6774 | 0.6522 | 0.9052 |
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+ | 0.0629 | 8.0 | 65880 | 0.4933 | 0.6332 | 0.6755 | 0.6537 | 0.9065 |
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+ | 0.0492 | 9.0 | 74115 | 0.5266 | 0.6360 | 0.6752 | 0.6550 | 0.9067 |
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+ | 0.0401 | 10.0 | 82350 | 0.5452 | 0.6340 | 0.6760 | 0.6543 | 0.9065 |
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  ### Framework versions
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