onionLad commited on
Commit
60a164f
1 Parent(s): 60a9a55

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +11 -11
README.md CHANGED
@@ -1,5 +1,5 @@
1
  ---
2
- license: apache-2.0
3
  tags:
4
  - generated_from_trainer
5
  metrics:
@@ -17,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
17
 
18
  # medlid-identify
19
 
20
- This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
21
  It achieves the following results on the evaluation set:
22
- - Loss: 0.1241
23
- - Precision: 0.3760
24
- - Recall: 0.4362
25
- - F1: 0.4038
26
- - Accuracy: 0.9601
27
 
28
  ## Model description
29
 
@@ -54,10 +54,10 @@ The following hyperparameters were used during training:
54
 
55
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
- | 0.1426 | 1.0 | 835 | 0.1035 | 0.2819 | 0.2529 | 0.2666 | 0.9603 |
58
- | 0.0852 | 2.0 | 1670 | 0.0975 | 0.3845 | 0.3259 | 0.3528 | 0.9636 |
59
- | 0.061 | 3.0 | 2505 | 0.1099 | 0.3832 | 0.4585 | 0.4175 | 0.9607 |
60
- | 0.0465 | 4.0 | 3340 | 0.1241 | 0.3760 | 0.4362 | 0.4038 | 0.9601 |
61
 
62
 
63
  ### Framework versions
 
1
  ---
2
+ license: mit
3
  tags:
4
  - generated_from_trainer
5
  metrics:
 
17
 
18
  # medlid-identify
19
 
20
+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 0.1248
23
+ - Precision: 0.4410
24
+ - Recall: 0.4209
25
+ - F1: 0.4307
26
+ - Accuracy: 0.9541
27
 
28
  ## Model description
29
 
 
54
 
55
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
+ | No log | 1.0 | 381 | 0.1297 | 0.3898 | 0.3032 | 0.3411 | 0.9525 |
58
+ | 0.1774 | 2.0 | 762 | 0.1191 | 0.4485 | 0.3489 | 0.3925 | 0.9551 |
59
+ | 0.1177 | 3.0 | 1143 | 0.1216 | 0.4341 | 0.4209 | 0.4274 | 0.9544 |
60
+ | 0.0974 | 4.0 | 1524 | 0.1248 | 0.4410 | 0.4209 | 0.4307 | 0.9541 |
61
 
62
 
63
  ### Framework versions