mdroth commited on
Commit
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1 Parent(s): 8339bf6
README.md CHANGED
@@ -1,8 +1,10 @@
1
  ---
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- license: apache-2.0
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- base_model: bert-base-cased
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - precision
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  - recall
@@ -10,7 +12,29 @@ metrics:
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  - accuracy
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  model-index:
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  - name: bert-finetuned-ner
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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
@@ -18,13 +42,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # bert-finetuned-ner
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- This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2040
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- - Precision: 0.8009
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- - Recall: 0.8341
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- - F1: 0.8171
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- - Accuracy: 0.9414
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  ## Model description
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@@ -44,8 +68,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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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
@@ -55,14 +79,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.1983 | 1.0 | 16471 | 0.1868 | 0.7919 | 0.8142 | 0.8029 | 0.9382 |
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- | 0.1527 | 2.0 | 32942 | 0.1889 | 0.7951 | 0.8344 | 0.8143 | 0.9406 |
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- | 0.1142 | 3.0 | 49413 | 0.2040 | 0.8009 | 0.8341 | 0.8171 | 0.9414 |
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  ### Framework versions
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- - Transformers 4.37.0
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- - Pytorch 2.1.2+cu118
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- - Datasets 2.16.1
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- - Tokenizers 0.15.1
 
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  ---
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+ license: mit
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+ base_model: FacebookAI/roberta-large
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - few-nerd
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  metrics:
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  - precision
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  - recall
 
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  - accuracy
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  model-index:
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  - name: bert-finetuned-ner
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: few-nerd
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+ type: few-nerd
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+ config: supervised
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+ split: validation
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+ args: supervised
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.7833402370948971
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+ - name: Recall
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+ type: recall
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+ value: 0.8147760612215589
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+ - name: F1
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+ type: f1
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+ value: 0.798748969206943
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9425415670481714
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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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  # bert-finetuned-ner
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+ This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the few-nerd dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2154
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+ - Precision: 0.7833
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+ - Recall: 0.8148
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+ - F1: 0.7987
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+ - Accuracy: 0.9425
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.1957 | 1.0 | 32942 | 0.1963 | 0.7533 | 0.7992 | 0.7756 | 0.9386 |
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+ | 0.1596 | 2.0 | 65884 | 0.2025 | 0.7768 | 0.8063 | 0.7913 | 0.9416 |
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+ | 0.1207 | 3.0 | 98826 | 0.2154 | 0.7833 | 0.8148 | 0.7987 | 0.9425 |
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  ### Framework versions
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.1+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
config.json CHANGED
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