crisU8 commited on
Commit
a0ee202
1 Parent(s): 6139835

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +67 -0
README.md ADDED
@@ -0,0 +1,67 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - generated_from_trainer
4
+ metrics:
5
+ - precision
6
+ - recall
7
+ - f1
8
+ - accuracy
9
+ model-index:
10
+ - name: bert-finetuned-ner-clinical-plncmm-large-25
11
+ results: []
12
+ ---
13
+
14
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
+ should probably proofread and complete it, then remove this comment. -->
16
+
17
+ # bert-finetuned-ner-clinical-plncmm-large-25
18
+
19
+ This model is a fine-tuned version of [plncmm/beto-clinical-wl-es](https://huggingface.co/plncmm/beto-clinical-wl-es) on the None dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 0.2487
22
+ - Precision: 0.7372
23
+ - Recall: 0.8035
24
+ - F1: 0.7689
25
+ - Accuracy: 0.9270
26
+
27
+ ## Model description
28
+
29
+ More information needed
30
+
31
+ ## Intended uses & limitations
32
+
33
+ More information needed
34
+
35
+ ## Training and evaluation data
36
+
37
+ More information needed
38
+
39
+ ## Training procedure
40
+
41
+ ### Training hyperparameters
42
+
43
+ The following hyperparameters were used during training:
44
+ - learning_rate: 3e-05
45
+ - train_batch_size: 18
46
+ - eval_batch_size: 32
47
+ - seed: 42
48
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
49
+ - lr_scheduler_type: linear
50
+ - lr_scheduler_warmup_steps: 400
51
+ - num_epochs: 3
52
+
53
+ ### Training results
54
+
55
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
+ | No log | 1.0 | 446 | 0.2607 | 0.6701 | 0.7772 | 0.7197 | 0.9113 |
58
+ | 0.6128 | 2.0 | 892 | 0.2298 | 0.7266 | 0.7964 | 0.7599 | 0.9254 |
59
+ | 0.1927 | 3.0 | 1338 | 0.2487 | 0.7372 | 0.8035 | 0.7689 | 0.9270 |
60
+
61
+
62
+ ### Framework versions
63
+
64
+ - Transformers 4.30.2
65
+ - Pytorch 2.0.1+cu118
66
+ - Datasets 2.13.1
67
+ - Tokenizers 0.13.3