Commit
·
6c03e95
1
Parent(s):
08ce254
add model
Browse files- README.md +102 -0
- logs/events.out.tfevents.1652723121.794725525cd1.71.0 +2 -2
- pytorch_model.bin +1 -1
README.md
ADDED
@@ -0,0 +1,102 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: mit
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
datasets:
|
6 |
+
- conll2003
|
7 |
+
metrics:
|
8 |
+
- precision
|
9 |
+
- recall
|
10 |
+
- f1
|
11 |
+
- accuracy
|
12 |
+
model-index:
|
13 |
+
- name: bert-to-distilbert-NER
|
14 |
+
results:
|
15 |
+
- task:
|
16 |
+
name: Token Classification
|
17 |
+
type: token-classification
|
18 |
+
dataset:
|
19 |
+
name: conll2003
|
20 |
+
type: conll2003
|
21 |
+
args: conll2003
|
22 |
+
metrics:
|
23 |
+
- name: Precision
|
24 |
+
type: precision
|
25 |
+
value: 0.014488935721812434
|
26 |
+
- name: Recall
|
27 |
+
type: recall
|
28 |
+
value: 0.018512285425782565
|
29 |
+
- name: F1
|
30 |
+
type: f1
|
31 |
+
value: 0.016255356878971478
|
32 |
+
- name: Accuracy
|
33 |
+
type: accuracy
|
34 |
+
value: 0.7597280273150055
|
35 |
+
---
|
36 |
+
|
37 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
38 |
+
should probably proofread and complete it, then remove this comment. -->
|
39 |
+
|
40 |
+
# bert-to-distilbert-NER
|
41 |
+
|
42 |
+
This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the conll2003 dataset.
|
43 |
+
It achieves the following results on the evaluation set:
|
44 |
+
- Loss: 44.0386
|
45 |
+
- Precision: 0.0145
|
46 |
+
- Recall: 0.0185
|
47 |
+
- F1: 0.0163
|
48 |
+
- Accuracy: 0.7597
|
49 |
+
|
50 |
+
## Model description
|
51 |
+
|
52 |
+
More information needed
|
53 |
+
|
54 |
+
## Intended uses & limitations
|
55 |
+
|
56 |
+
More information needed
|
57 |
+
|
58 |
+
## Training and evaluation data
|
59 |
+
|
60 |
+
More information needed
|
61 |
+
|
62 |
+
## Training procedure
|
63 |
+
|
64 |
+
### Training hyperparameters
|
65 |
+
|
66 |
+
The following hyperparameters were used during training:
|
67 |
+
- learning_rate: 6e-05
|
68 |
+
- train_batch_size: 128
|
69 |
+
- eval_batch_size: 128
|
70 |
+
- seed: 33
|
71 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
72 |
+
- lr_scheduler_type: linear
|
73 |
+
- num_epochs: 15
|
74 |
+
- mixed_precision_training: Native AMP
|
75 |
+
|
76 |
+
### Training results
|
77 |
+
|
78 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
79 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
80 |
+
| 201.4012 | 1.0 | 110 | 133.7231 | 0.0153 | 0.0106 | 0.0125 | 0.7539 |
|
81 |
+
| 106.9317 | 2.0 | 220 | 99.3629 | 0.0266 | 0.0305 | 0.0284 | 0.7593 |
|
82 |
+
| 81.3601 | 3.0 | 330 | 80.3763 | 0.0159 | 0.0214 | 0.0183 | 0.7604 |
|
83 |
+
| 63.8325 | 4.0 | 440 | 67.7620 | 0.0179 | 0.0244 | 0.0207 | 0.7599 |
|
84 |
+
| 52.0271 | 5.0 | 550 | 59.0806 | 0.0203 | 0.0268 | 0.0231 | 0.7598 |
|
85 |
+
| 44.4419 | 6.0 | 660 | 55.3208 | 0.0211 | 0.0278 | 0.0240 | 0.7603 |
|
86 |
+
| 39.2351 | 7.0 | 770 | 52.4510 | 0.0170 | 0.0222 | 0.0193 | 0.7598 |
|
87 |
+
| 35.3438 | 8.0 | 880 | 50.4576 | 0.0205 | 0.0268 | 0.0232 | 0.7604 |
|
88 |
+
| 32.7385 | 9.0 | 990 | 48.3418 | 0.0173 | 0.0227 | 0.0197 | 0.7595 |
|
89 |
+
| 30.6531 | 10.0 | 1100 | 46.7304 | 0.0147 | 0.0188 | 0.0165 | 0.7600 |
|
90 |
+
| 29.0811 | 11.0 | 1210 | 46.3386 | 0.0151 | 0.0190 | 0.0168 | 0.7599 |
|
91 |
+
| 27.9501 | 12.0 | 1320 | 45.4516 | 0.0163 | 0.0204 | 0.0181 | 0.7604 |
|
92 |
+
| 26.7452 | 13.0 | 1430 | 44.3425 | 0.0154 | 0.0199 | 0.0173 | 0.7592 |
|
93 |
+
| 25.5367 | 14.0 | 1540 | 44.0415 | 0.0146 | 0.0190 | 0.0165 | 0.7594 |
|
94 |
+
| 24.5507 | 15.0 | 1650 | 44.0386 | 0.0145 | 0.0185 | 0.0163 | 0.7597 |
|
95 |
+
|
96 |
+
|
97 |
+
### Framework versions
|
98 |
+
|
99 |
+
- Transformers 4.19.1
|
100 |
+
- Pytorch 1.11.0+cu113
|
101 |
+
- Datasets 2.2.1
|
102 |
+
- Tokenizers 0.12.1
|
logs/events.out.tfevents.1652723121.794725525cd1.71.0
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3a31bd9996a4aabbe4741d5185f707e4b9b7cc9a8a66e7fb0b519070e2465558
|
3 |
+
size 13654
|
pytorch_model.bin
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 260835441
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ce595d0bc7d50e6f89da3fd2c476e0c5917dd750eedccfbfd9c134a26594ef06
|
3 |
size 260835441
|