Hugging Face's logo

aiface
/
ModernBERT-large_v3

Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
Model card Files
xet
Community
aiface commited on
Commit
8ef386f
·
verified ·
1 Parent(s): 8644880

Model save

Browse files
Files changed (4) hide show
  1. README.md +87 -0
  2. classification_report_test.txt +14 -0
  3. confusion_matrix_test.csv +4 -0
  4. model.safetensors +1 -1
README.md ADDED
@@ -0,0 +1,87 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: apache-2.0
4
+ base_model: answerdotai/ModernBERT-large
5
+ tags:
6
+ - generated_from_trainer
7
+ metrics:
8
+ - accuracy
9
+ model-index:
10
+ - name: ModernBERT-large_v3
11
+ results: []
12
+ ---
13
+
14
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
+ should probably proofread and complete it, then remove this comment. -->
16
+
17
+ # ModernBERT-large_v3
18
+
19
+ This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 0.8266
22
+ - Accuracy: 0.9109
23
+ - Precision Macro: 0.7681
24
+ - Recall Macro: 0.7438
25
+ - F1 Macro: 0.7542
26
+ - F1 Weighted: 0.9084
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: 5e-05
46
+ - train_batch_size: 32
47
+ - eval_batch_size: 32
48
+ - seed: 42
49
+ - gradient_accumulation_steps: 2
50
+ - total_train_batch_size: 64
51
+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
52
+ - lr_scheduler_type: linear
53
+ - num_epochs: 20
54
+ - mixed_precision_training: Native AMP
55
+
56
+ ### Training results
57
+
58
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | F1 Weighted |
59
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:-----------:|
60
+ | 0.9719 | 1.0 | 179 | 0.4542 | 0.8484 | 0.7048 | 0.5982 | 0.5951 | 0.8301 |
61
+ | 0.6216 | 2.0 | 358 | 0.3472 | 0.8819 | 0.8897 | 0.6468 | 0.6648 | 0.8674 |
62
+ | 0.5377 | 3.0 | 537 | 0.3063 | 0.8926 | 0.7740 | 0.7326 | 0.7477 | 0.8893 |
63
+ | 0.4253 | 4.0 | 716 | 0.2703 | 0.9109 | 0.8330 | 0.7357 | 0.7651 | 0.9053 |
64
+ | 0.3699 | 5.0 | 895 | 0.2795 | 0.9090 | 0.7756 | 0.7968 | 0.7850 | 0.9107 |
65
+ | 0.2003 | 6.0 | 1074 | 0.3297 | 0.9128 | 0.8225 | 0.7620 | 0.7848 | 0.9094 |
66
+ | 0.1596 | 7.0 | 1253 | 0.3799 | 0.9097 | 0.7673 | 0.7805 | 0.7734 | 0.9109 |
67
+ | 0.0876 | 8.0 | 1432 | 0.5013 | 0.9236 | 0.8343 | 0.7899 | 0.8084 | 0.9214 |
68
+ | 0.0598 | 9.0 | 1611 | 0.5279 | 0.9185 | 0.8126 | 0.7621 | 0.7815 | 0.9152 |
69
+ | 0.054 | 10.0 | 1790 | 0.5909 | 0.9109 | 0.7998 | 0.7728 | 0.7847 | 0.9092 |
70
+ | 0.0419 | 11.0 | 1969 | 0.7661 | 0.9141 | 0.7877 | 0.7427 | 0.7594 | 0.9102 |
71
+ | 0.0108 | 12.0 | 2148 | 0.9184 | 0.9185 | 0.8260 | 0.7337 | 0.7601 | 0.9122 |
72
+ | 0.0177 | 13.0 | 2327 | 0.8254 | 0.9128 | 0.7820 | 0.7494 | 0.7628 | 0.9099 |
73
+ | 0.0013 | 14.0 | 2506 | 0.8059 | 0.9103 | 0.7741 | 0.7391 | 0.7531 | 0.9069 |
74
+ | 0.0019 | 15.0 | 2685 | 0.8174 | 0.9078 | 0.7620 | 0.7502 | 0.7556 | 0.9065 |
75
+ | 0.0028 | 16.0 | 2864 | 0.8202 | 0.9109 | 0.7704 | 0.7438 | 0.7550 | 0.9082 |
76
+ | 0.0 | 17.0 | 3043 | 0.8126 | 0.9103 | 0.7678 | 0.7433 | 0.7537 | 0.9078 |
77
+ | 0.0008 | 18.0 | 3222 | 0.8319 | 0.9109 | 0.7734 | 0.7482 | 0.7589 | 0.9085 |
78
+ | 0.0 | 19.0 | 3401 | 0.8245 | 0.9116 | 0.7686 | 0.7443 | 0.7546 | 0.9090 |
79
+ | 0.0001 | 20.0 | 3580 | 0.8266 | 0.9109 | 0.7681 | 0.7438 | 0.7542 | 0.9084 |
80
+
81
+
82
+ ### Framework versions
83
+
84
+ - Transformers 4.55.0
85
+ - Pytorch 2.7.0+cu126
86
+ - Datasets 4.0.0
87
+ - Tokenizers 0.21.4
classification_report_test.txt ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ precision recall f1-score support
2
+
3
+ negative 0.89 0.95 0.92 1409
4
+ neutral 0.54 0.28 0.37 167
5
+ positive 0.92 0.92 0.92 1590
6
+
7
+ accuracy 0.90 3166
8
+ macro avg 0.78 0.71 0.74 3166
9
+ weighted avg 0.89 0.90 0.89 3166
10
+
11
+ Confusion matrix:
12
+ [[1333 20 56]
13
+ [ 57 47 63]
14
+ [ 114 20 1456]]
confusion_matrix_test.csv ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ ,negative,neutral,positive
2
+ negative,1333,20,56
3
+ neutral,57,47,63
4
+ positive,114,20,1456
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e4a304c1df9451725f4563fedec0c1fcc5afea379abae7728ee653642c36ef55
3
  size 1583355740
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f3256d32363453ede2f913979f89407a718a84f003f598daf1ef3954ad99ed53
3
  size 1583355740