Hugging Face's logo

thusken
/
nb-bert-base-user-needs

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
2
thusken commited on
Commit
688bd9f
·
1 Parent(s): ef303d8

End of training

Browse files
Files changed (2) hide show
  1. README.md +31 -16
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
19
 
20
  This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on the None dataset.
21
  It achieves the following results on the evaluation set:
22
- - Loss: 0.6468
23
- - Accuracy: 0.8582
24
- - F1: 0.8388
25
- - Precision: 0.8295
26
- - Recall: 0.8582
27
 
28
  ## Model description
29
 
@@ -49,23 +49,38 @@ The following hyperparameters were used during training:
49
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
  - lr_scheduler_type: linear
51
  - lr_scheduler_warmup_steps: 500
52
- - num_epochs: 10
53
  - mixed_precision_training: Native AMP
54
 
55
  ### Training results
56
 
57
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
58
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
59
- | No log | 1.0 | 98 | 1.2122 | 0.6005 | 0.4506 | 0.3606 | 0.6005 |
60
- | No log | 2.0 | 196 | 0.9735 | 0.7113 | 0.6231 | 0.5549 | 0.7113 |
61
- | No log | 3.0 | 294 | 0.7894 | 0.7655 | 0.6996 | 0.7399 | 0.7655 |
62
- | No log | 4.0 | 392 | 0.9499 | 0.6933 | 0.6584 | 0.6617 | 0.6933 |
63
- | No log | 5.0 | 490 | 0.7529 | 0.7784 | 0.7217 | 0.7107 | 0.7784 |
64
- | 0.9006 | 6.0 | 588 | 0.7510 | 0.7964 | 0.7491 | 0.7370 | 0.7964 |
65
- | 0.9006 | 7.0 | 686 | 0.5963 | 0.8273 | 0.8044 | 0.7960 | 0.8273 |
66
- | 0.9006 | 8.0 | 784 | 0.6918 | 0.8351 | 0.8071 | 0.8096 | 0.8351 |
67
- | 0.9006 | 9.0 | 882 | 0.7391 | 0.8273 | 0.8017 | 0.8042 | 0.8273 |
68
- | 0.9006 | 10.0 | 980 | 0.6468 | 0.8582 | 0.8388 | 0.8295 | 0.8582 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
69
 
70
 
71
  ### Framework versions
 
19
 
20
  This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on the None dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 1.0600
23
+ - Accuracy: 0.8479
24
+ - F1: 0.8319
25
+ - Precision: 0.8315
26
+ - Recall: 0.8479
27
 
28
  ## Model description
29
 
 
49
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
  - lr_scheduler_type: linear
51
  - lr_scheduler_warmup_steps: 500
52
+ - num_epochs: 25
53
  - mixed_precision_training: Native AMP
54
 
55
  ### Training results
56
 
57
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
58
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
59
+ | No log | 1.0 | 98 | 1.1222 | 0.6263 | 0.5185 | 0.5076 | 0.6263 |
60
+ | No log | 2.0 | 196 | 1.0066 | 0.7216 | 0.6436 | 0.5899 | 0.7216 |
61
+ | No log | 3.0 | 294 | 0.8540 | 0.7577 | 0.7037 | 0.6760 | 0.7577 |
62
+ | No log | 4.0 | 392 | 0.8621 | 0.7603 | 0.6998 | 0.6568 | 0.7603 |
63
+ | No log | 5.0 | 490 | 0.8062 | 0.7887 | 0.7500 | 0.7449 | 0.7887 |
64
+ | 0.91 | 6.0 | 588 | 0.7465 | 0.8041 | 0.7660 | 0.7636 | 0.8041 |
65
+ | 0.91 | 7.0 | 686 | 0.6324 | 0.8247 | 0.8163 | 0.8187 | 0.8247 |
66
+ | 0.91 | 8.0 | 784 | 0.7333 | 0.7964 | 0.7703 | 0.7740 | 0.7964 |
67
+ | 0.91 | 9.0 | 882 | 0.6590 | 0.8325 | 0.8208 | 0.8106 | 0.8325 |
68
+ | 0.91 | 10.0 | 980 | 0.9854 | 0.8196 | 0.7890 | 0.7920 | 0.8196 |
69
+ | 0.4246 | 11.0 | 1078 | 0.7023 | 0.8247 | 0.8054 | 0.8138 | 0.8247 |
70
+ | 0.4246 | 12.0 | 1176 | 0.8995 | 0.8325 | 0.8120 | 0.8068 | 0.8325 |
71
+ | 0.4246 | 13.0 | 1274 | 0.8589 | 0.8299 | 0.8145 | 0.8058 | 0.8299 |
72
+ | 0.4246 | 14.0 | 1372 | 0.9859 | 0.8376 | 0.8151 | 0.8123 | 0.8376 |
73
+ | 0.4246 | 15.0 | 1470 | 0.8452 | 0.8402 | 0.8318 | 0.8341 | 0.8402 |
74
+ | 0.1637 | 16.0 | 1568 | 1.1156 | 0.8351 | 0.8157 | 0.8196 | 0.8351 |
75
+ | 0.1637 | 17.0 | 1666 | 1.1514 | 0.8325 | 0.8122 | 0.8218 | 0.8325 |
76
+ | 0.1637 | 18.0 | 1764 | 1.0092 | 0.8428 | 0.8266 | 0.8320 | 0.8428 |
77
+ | 0.1637 | 19.0 | 1862 | 1.0368 | 0.8351 | 0.8229 | 0.8287 | 0.8351 |
78
+ | 0.1637 | 20.0 | 1960 | 1.0600 | 0.8479 | 0.8319 | 0.8315 | 0.8479 |
79
+ | 0.0391 | 21.0 | 2058 | 1.1046 | 0.8428 | 0.8293 | 0.8269 | 0.8428 |
80
+ | 0.0391 | 22.0 | 2156 | 1.1178 | 0.8454 | 0.8262 | 0.8280 | 0.8454 |
81
+ | 0.0391 | 23.0 | 2254 | 1.1103 | 0.8428 | 0.8268 | 0.8295 | 0.8428 |
82
+ | 0.0391 | 24.0 | 2352 | 1.1179 | 0.8428 | 0.8274 | 0.8313 | 0.8428 |
83
+ | 0.0391 | 25.0 | 2450 | 1.1134 | 0.8402 | 0.8233 | 0.8254 | 0.8402 |
84
 
85
 
86
  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:f4f43aecdb33cd129e2d9d8efbc8878f1dc151323d4dbc513e659dd8b8e1685e
3
  size 711517229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:de1c79f804196a2fe496dd6b38108fbe4b4614c99642d1f6ecddad5d81f469d2
3
  size 711517229