Hugging Face's logo

joshuaphua
/
bert-base-uncased-conll2003

Token Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
1
joshuaphua commited on
Commit
1f148fa
•
1 Parent(s): e3ca48b

End of training

Browse files
Files changed (2) hide show
  1. README.md +13 -13
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
25
  metrics:
26
  - name: Precision
27
  type: precision
28
- value: 0.8926710663424801
29
  - name: Recall
30
  type: recall
31
- value: 0.910056657223796
32
  - name: F1
33
  type: f1
34
- value: 0.9012800280554094
35
  - name: Accuracy
36
  type: accuracy
37
- value: 0.9784860557768924
38
  ---
39
 
40
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
44
 
45
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.
46
  It achieves the following results on the evaluation set:
47
- - Loss: 0.1448
48
- - Precision: 0.8927
49
- - Recall: 0.9101
50
- - F1: 0.9013
51
- - Accuracy: 0.9785
52
 
53
  ## Model description
54
 
@@ -79,13 +79,13 @@ The following hyperparameters were used during training:
79
 
80
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
81
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
82
- | 0.062 | 1.0 | 3922 | 0.1196 | 0.8913 | 0.9014 | 0.8963 | 0.9784 |
83
- | 0.024 | 2.0 | 7844 | 0.1448 | 0.8927 | 0.9101 | 0.9013 | 0.9785 |
84
 
85
 
86
  ### Framework versions
87
 
88
- - Transformers 4.44.0
89
  - Pytorch 2.2.2
90
  - Datasets 2.20.0
91
- - Tokenizers 0.19.1
 
25
  metrics:
26
  - name: Precision
27
  type: precision
28
+ value: 0.8908045977011494
29
  - name: Recall
30
  type: recall
31
+ value: 0.9056303116147308
32
  - name: F1
33
  type: f1
34
+ value: 0.8981562774363476
35
  - name: Accuracy
36
  type: accuracy
37
+ value: 0.9781845590610531
38
  ---
39
 
40
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
44
 
45
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.
46
  It achieves the following results on the evaluation set:
47
+ - Loss: 0.1539
48
+ - Precision: 0.8908
49
+ - Recall: 0.9056
50
+ - F1: 0.8982
51
+ - Accuracy: 0.9782
52
 
53
  ## Model description
54
 
 
79
 
80
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
81
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
82
+ | 0.0641 | 1.0 | 3922 | 0.1398 | 0.8868 | 0.9044 | 0.8955 | 0.9776 |
83
+ | 0.0262 | 2.0 | 7844 | 0.1539 | 0.8908 | 0.9056 | 0.8982 | 0.9782 |
84
 
85
 
86
  ### Framework versions
87
 
88
+ - Transformers 4.33.2
89
  - Pytorch 2.2.2
90
  - Datasets 2.20.0
91
+ - Tokenizers 0.13.3
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d0bf78615a9f792a557aa12d69cabc3e3d060ae57370906c1cd7999539dd2dcb
3
  size 435659622
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5d002ad6b73d7b2b3eabd57d90e1308583ec30151ead54cfdbff5e58699deff4
3
  size 435659622