dondosss commited on
Commit
deaecbf
1 Parent(s): bec1571

Training complete

Browse files
Files changed (1) hide show
  1. README.md +68 -0
README.md ADDED
@@ -0,0 +1,68 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: DeepPavlov/rubert-base-cased
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - precision
7
+ - recall
8
+ - f1
9
+ - accuracy
10
+ model-index:
11
+ - name: rubert-finetuned-ner
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
+ # rubert-finetuned-ner
19
+
20
+ This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on an unknown dataset.
21
+ It achieves the following results on the evaluation set:
22
+ - Loss: 0.1466
23
+ - Precision: 0.8876
24
+ - Recall: 0.9075
25
+ - F1: 0.8975
26
+ - Accuracy: 0.9608
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: 2e-05
46
+ - train_batch_size: 64
47
+ - eval_batch_size: 128
48
+ - seed: 42
49
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
+ - lr_scheduler_type: linear
51
+ - lr_scheduler_warmup_ratio: 0.05
52
+ - num_epochs: 3
53
+
54
+ ### Training results
55
+
56
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
57
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
58
+ | No log | 1.0 | 313 | 0.1607 | 0.8568 | 0.8831 | 0.8697 | 0.9542 |
59
+ | 0.3113 | 2.0 | 626 | 0.1510 | 0.8780 | 0.9025 | 0.8901 | 0.9579 |
60
+ | 0.3113 | 3.0 | 939 | 0.1466 | 0.8876 | 0.9075 | 0.8975 | 0.9608 |
61
+
62
+
63
+ ### Framework versions
64
+
65
+ - Transformers 4.38.2
66
+ - Pytorch 2.2.1+cu121
67
+ - Datasets 2.18.0
68
+ - Tokenizers 0.15.2