aimarsg commited on
Commit
d846858
1 Parent(s): ff7a50b

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +94 -0
README.md ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - precision
7
+ - recall
8
+ - f1
9
+ - accuracy
10
+ model-index:
11
+ - name: prueba3
12
+ results: []
13
+ ---
14
+
15
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
16
+ should probably proofread and complete it, then remove this comment. -->
17
+
18
+ # prueba3
19
+
20
+ This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer) on an unknown dataset.
21
+ It achieves the following results on the evaluation set:
22
+ - Loss: 0.2158
23
+ - Precision: 0.7162
24
+ - Recall: 0.6335
25
+ - F1: 0.6723
26
+ - Accuracy: 0.9737
27
+
28
+ ## Model description
29
+
30
+ More information needed
31
+
32
+ ## Intended uses & limitations
33
+
34
+ More information needed
35
+
36
+ ## Training and evaluation data
37
+
38
+ More information needed
39
+
40
+ ## Training procedure
41
+
42
+ ### Training hyperparameters
43
+
44
+ The following hyperparameters were used during training:
45
+ - learning_rate: 2.75e-05
46
+ - train_batch_size: 32
47
+ - eval_batch_size: 8
48
+ - seed: 42
49
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
+ - lr_scheduler_type: linear
51
+ - num_epochs: 30
52
+
53
+ ### Training results
54
+
55
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
+ | No log | 1.0 | 29 | 0.2562 | 0.7732 | 0.5976 | 0.6742 | 0.9719 |
58
+ | No log | 2.0 | 58 | 0.2526 | 0.705 | 0.5618 | 0.6253 | 0.9704 |
59
+ | No log | 3.0 | 87 | 0.2187 | 0.6833 | 0.6534 | 0.6680 | 0.9705 |
60
+ | No log | 4.0 | 116 | 0.2205 | 0.6583 | 0.6295 | 0.6436 | 0.9715 |
61
+ | No log | 5.0 | 145 | 0.2161 | 0.7162 | 0.6534 | 0.6833 | 0.9712 |
62
+ | No log | 6.0 | 174 | 0.2293 | 0.6977 | 0.5976 | 0.6438 | 0.9722 |
63
+ | No log | 7.0 | 203 | 0.2207 | 0.6972 | 0.6056 | 0.6482 | 0.9724 |
64
+ | No log | 8.0 | 232 | 0.2343 | 0.6781 | 0.6295 | 0.6529 | 0.9707 |
65
+ | No log | 9.0 | 261 | 0.2212 | 0.7115 | 0.5896 | 0.6449 | 0.9730 |
66
+ | No log | 10.0 | 290 | 0.2171 | 0.7260 | 0.6016 | 0.6580 | 0.9734 |
67
+ | No log | 11.0 | 319 | 0.2191 | 0.6851 | 0.6414 | 0.6626 | 0.9725 |
68
+ | No log | 12.0 | 348 | 0.2101 | 0.7056 | 0.6494 | 0.6763 | 0.9740 |
69
+ | No log | 13.0 | 377 | 0.2227 | 0.7240 | 0.6375 | 0.6780 | 0.9732 |
70
+ | No log | 14.0 | 406 | 0.2226 | 0.7442 | 0.6375 | 0.6867 | 0.9739 |
71
+ | No log | 15.0 | 435 | 0.2247 | 0.7339 | 0.6375 | 0.6823 | 0.9739 |
72
+ | No log | 16.0 | 464 | 0.2167 | 0.6983 | 0.6454 | 0.6708 | 0.9729 |
73
+ | No log | 17.0 | 493 | 0.2220 | 0.7281 | 0.6295 | 0.6752 | 0.9732 |
74
+ | 0.0005 | 18.0 | 522 | 0.2294 | 0.7299 | 0.6135 | 0.6667 | 0.9725 |
75
+ | 0.0005 | 19.0 | 551 | 0.2104 | 0.6949 | 0.6534 | 0.6735 | 0.9722 |
76
+ | 0.0005 | 20.0 | 580 | 0.2103 | 0.7240 | 0.6375 | 0.6780 | 0.9730 |
77
+ | 0.0005 | 21.0 | 609 | 0.2092 | 0.7137 | 0.6454 | 0.6778 | 0.9735 |
78
+ | 0.0005 | 22.0 | 638 | 0.2091 | 0.7181 | 0.6494 | 0.6820 | 0.9737 |
79
+ | 0.0005 | 23.0 | 667 | 0.2081 | 0.7162 | 0.6534 | 0.6833 | 0.9735 |
80
+ | 0.0005 | 24.0 | 696 | 0.2198 | 0.7264 | 0.6135 | 0.6652 | 0.9722 |
81
+ | 0.0005 | 25.0 | 725 | 0.2206 | 0.7290 | 0.6215 | 0.6710 | 0.9725 |
82
+ | 0.0005 | 26.0 | 754 | 0.2194 | 0.7256 | 0.6215 | 0.6695 | 0.9735 |
83
+ | 0.0005 | 27.0 | 783 | 0.2220 | 0.7290 | 0.6215 | 0.6710 | 0.9739 |
84
+ | 0.0005 | 28.0 | 812 | 0.2230 | 0.7290 | 0.6215 | 0.6710 | 0.9735 |
85
+ | 0.0005 | 29.0 | 841 | 0.2163 | 0.7182 | 0.6295 | 0.6709 | 0.9737 |
86
+ | 0.0005 | 30.0 | 870 | 0.2158 | 0.7162 | 0.6335 | 0.6723 | 0.9737 |
87
+
88
+
89
+ ### Framework versions
90
+
91
+ - Transformers 4.27.3
92
+ - Pytorch 1.13.1+cu116
93
+ - Datasets 2.10.1
94
+ - Tokenizers 0.13.2