gagan3012 commited on
Commit
45b1187
1 Parent(s): b5908f5
README.md CHANGED
@@ -22,16 +22,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.8898342059336823
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  - name: Recall
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  type: recall
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- value: 0.9126300481038148
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  - name: F1
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  type: f1
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- value: 0.9010879770254598
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  - name: Accuracy
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  type: accuracy
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- value: 0.977902044577184
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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
@@ -41,11 +41,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0801
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- - Precision: 0.8898
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- - Recall: 0.9126
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- - F1: 0.9011
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- - Accuracy: 0.9779
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  ## Model description
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@@ -70,18 +70,20 @@ 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: 1
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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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- | 0.2425 | 1.0 | 878 | 0.0801 | 0.8898 | 0.9126 | 0.9011 | 0.9779 |
 
 
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  ### Framework versions
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- - Transformers 4.10.0
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  - Pytorch 1.9.0+cu102
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- - Datasets 1.11.0
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  - Tokenizers 0.10.3
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.9274238227146815
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  - name: Recall
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  type: recall
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+ value: 0.9363463474661595
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  - name: F1
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  type: f1
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+ value: 0.9318637274549098
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9839865283492462
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0614
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+ - Precision: 0.9274
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+ - Recall: 0.9363
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+ - F1: 0.9319
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+ - Accuracy: 0.9840
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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: 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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+ | 0.2403 | 1.0 | 878 | 0.0701 | 0.9101 | 0.9202 | 0.9151 | 0.9805 |
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+ | 0.0508 | 2.0 | 1756 | 0.0600 | 0.9220 | 0.9350 | 0.9285 | 0.9833 |
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+ | 0.0301 | 3.0 | 2634 | 0.0614 | 0.9274 | 0.9363 | 0.9319 | 0.9840 |
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  ### Framework versions
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+ - Transformers 4.10.2
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  - Pytorch 1.9.0+cu102
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+ - Datasets 1.12.0
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  - Tokenizers 0.10.3
config.json CHANGED
@@ -41,6 +41,6 @@
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  }
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  "sinusoidal_pos_embds": false,
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  "tie_weights_": true,
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  "torch_dtype": "float32",
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  "vocab_size": 30522
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