Hugging Face's logo

pabRomero
/
PubMedBERT-full-finetuned-ner-pablo

Token Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
pabRomero commited on
Commit
78bdf3e
•
1 Parent(s): 9117c3c

Training complete

Browse files
Files changed (2) hide show
  1. README.md +75 -74
  2. runs/Aug23_14-27-56_ee1898c059d7/events.out.tfevents.1724423277.ee1898c059d7.1664.8 +2 -2
README.md CHANGED
@@ -1,74 +1,75 @@
1
- ---
2
- license: mit
3
- base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
4
- tags:
5
- - generated_from_trainer
6
- metrics:
7
- - precision
8
- - recall
9
- - f1
10
- - accuracy
11
- model-index:
12
- - name: PubMedBERT-full-finetuned-ner-pablo
13
- results: []
14
- ---
15
-
16
- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
- should probably proofread and complete it, then remove this comment. -->
18
-
19
- # PubMedBERT-full-finetuned-ner-pablo
20
-
21
- This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on the None dataset.
22
- It achieves the following results on the evaluation set:
23
- - Loss: 0.1043
24
- - Precision: 0.8193
25
- - Recall: 0.7977
26
- - F1: 0.8083
27
- - Accuracy: 0.9738
28
-
29
- ## Model description
30
-
31
- More information needed
32
-
33
- ## Intended uses & limitations
34
-
35
- More information needed
36
-
37
- ## Training and evaluation data
38
-
39
- More information needed
40
-
41
- ## Training procedure
42
-
43
- ### Training hyperparameters
44
-
45
- The following hyperparameters were used during training:
46
- - learning_rate: 0.0002
47
- - train_batch_size: 16
48
- - eval_batch_size: 16
49
- - seed: 42
50
- - gradient_accumulation_steps: 4
51
- - total_train_batch_size: 64
52
- - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
53
- - lr_scheduler_type: linear
54
- - lr_scheduler_warmup_ratio: 0.05
55
- - num_epochs: 5
56
- - mixed_precision_training: Native AMP
57
-
58
- ### Training results
59
-
60
- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
61
- |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
62
- | 0.2982 | 0.9996 | 652 | 0.1275 | 0.7749 | 0.7270 | 0.7502 | 0.9681 |
63
- | 0.1264 | 1.9992 | 1304 | 0.1043 | 0.7965 | 0.7654 | 0.7806 | 0.9709 |
64
- | 0.0876 | 2.9989 | 1956 | 0.0963 | 0.8097 | 0.7785 | 0.7938 | 0.9728 |
65
- | 0.0561 | 4.0 | 2609 | 0.0962 | 0.8224 | 0.7976 | 0.8098 | 0.9735 |
66
- | 0.0457 | 4.9981 | 3260 | 0.1043 | 0.8193 | 0.7977 | 0.8083 | 0.9738 |
67
-
68
-
69
- ### Framework versions
70
-
71
- - Transformers 4.44.0
72
- - Pytorch 2.4.0+cu124
73
- - Datasets 2.21.0
74
- - Tokenizers 0.19.1
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: mit
4
+ base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
5
+ tags:
6
+ - generated_from_trainer
7
+ metrics:
8
+ - precision
9
+ - recall
10
+ - f1
11
+ - accuracy
12
+ model-index:
13
+ - name: PubMedBERT-full-finetuned-ner-pablo
14
+ results: []
15
+ ---
16
+
17
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
18
+ should probably proofread and complete it, then remove this comment. -->
19
+
20
+ # PubMedBERT-full-finetuned-ner-pablo
21
+
22
+ This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on the None dataset.
23
+ It achieves the following results on the evaluation set:
24
+ - Loss: 0.0905
25
+ - Precision: 0.8142
26
+ - Recall: 0.8048
27
+ - F1: 0.8095
28
+ - Accuracy: 0.9771
29
+
30
+ ## Model description
31
+
32
+ More information needed
33
+
34
+ ## Intended uses & limitations
35
+
36
+ More information needed
37
+
38
+ ## Training and evaluation data
39
+
40
+ More information needed
41
+
42
+ ## Training procedure
43
+
44
+ ### Training hyperparameters
45
+
46
+ The following hyperparameters were used during training:
47
+ - learning_rate: 0.0002
48
+ - train_batch_size: 16
49
+ - eval_batch_size: 16
50
+ - seed: 42
51
+ - gradient_accumulation_steps: 4
52
+ - total_train_batch_size: 64
53
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
54
+ - lr_scheduler_type: linear
55
+ - lr_scheduler_warmup_ratio: 0.05
56
+ - num_epochs: 5
57
+ - mixed_precision_training: Native AMP
58
+
59
+ ### Training results
60
+
61
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
62
+ |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
63
+ | No log | 0.9970 | 252 | 0.0892 | 0.7631 | 0.7751 | 0.7690 | 0.9751 |
64
+ | 0.1853 | 1.9980 | 505 | 0.0802 | 0.8139 | 0.7876 | 0.8005 | 0.9780 |
65
+ | 0.1853 | 2.9990 | 758 | 0.0792 | 0.7994 | 0.7984 | 0.7989 | 0.9767 |
66
+ | 0.0461 | 4.0 | 1011 | 0.0788 | 0.8134 | 0.8045 | 0.8089 | 0.9780 |
67
+ | 0.0461 | 4.9852 | 1260 | 0.0905 | 0.8142 | 0.8048 | 0.8095 | 0.9771 |
68
+
69
+
70
+ ### Framework versions
71
+
72
+ - Transformers 4.44.2
73
+ - Pytorch 2.4.0+cu121
74
+ - Datasets 2.21.0
75
+ - Tokenizers 0.19.1
runs/Aug23_14-27-56_ee1898c059d7/events.out.tfevents.1724423277.ee1898c059d7.1664.8 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:04a0c64857d85be5c93dd12f9c6e3f0febfcf493bfe0e3f2c2c5f95feb54fe90
3
- size 8068
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:067815d1bb6a9343d7b9ce35b9f84b2d62db6acaf26f3aca0258e9a3a4db2b0b
3
+ size 8894