Hugging Face's logo

aiface
/
twitter-roberta-base-sentiment-latest_v3_scratch

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
Model card Files
xet
Community
aiface commited on
Commit
31b8988
·
verified ·
1 Parent(s): 7c1ab37

Model save

Browse files
Files changed (5) hide show
  1. README.md +108 -0
  2. classification_report_test.txt +14 -0
  3. confusion_matrix_test.csv +4 -0
  4. model.safetensors +1 -1
  5. model_predict.csv +0 -0
README.md ADDED
@@ -0,0 +1,108 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: cc-by-4.0
4
+ base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
5
+ tags:
6
+ - generated_from_trainer
7
+ metrics:
8
+ - accuracy
9
+ model-index:
10
+ - name: twitter-roberta-base-sentiment-latest_v3_scratch
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
+ # twitter-roberta-base-sentiment-latest_v3_scratch
18
+
19
+ This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 0.9484
22
+ - Accuracy: 0.8522
23
+ - Precision Macro: 0.7150
24
+ - Recall Macro: 0.6816
25
+ - F1 Macro: 0.6946
26
+ - F1 Weighted: 0.8484
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: 0.0001
46
+ - train_batch_size: 64
47
+ - eval_batch_size: 64
48
+ - seed: 42
49
+ - gradient_accumulation_steps: 4
50
+ - total_train_batch_size: 256
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: cosine
53
+ - lr_scheduler_warmup_ratio: 0.1
54
+ - num_epochs: 40
55
+ - mixed_precision_training: Native AMP
56
+
57
+ ### Training results
58
+
59
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | F1 Weighted |
60
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:-----------:|
61
+ | No log | 1.0 | 45 | 0.7207 | 0.6728 | 0.4697 | 0.4605 | 0.4446 | 0.6413 |
62
+ | 0.8468 | 2.0 | 90 | 0.7087 | 0.6721 | 0.5134 | 0.4813 | 0.4506 | 0.6414 |
63
+ | 0.7104 | 3.0 | 135 | 0.5202 | 0.7979 | 0.5365 | 0.5604 | 0.5445 | 0.7796 |
64
+ | 0.6128 | 4.0 | 180 | 0.5060 | 0.8105 | 0.7116 | 0.6006 | 0.6166 | 0.7984 |
65
+ | 0.505 | 5.0 | 225 | 0.4700 | 0.8212 | 0.7406 | 0.6029 | 0.6075 | 0.8079 |
66
+ | 0.446 | 6.0 | 270 | 0.5124 | 0.8143 | 0.5551 | 0.5735 | 0.5559 | 0.7957 |
67
+ | 0.4095 | 7.0 | 315 | 0.4568 | 0.8408 | 0.6926 | 0.6578 | 0.6700 | 0.8360 |
68
+ | 0.413 | 8.0 | 360 | 0.4471 | 0.8484 | 0.5658 | 0.5917 | 0.5783 | 0.8282 |
69
+ | 0.3451 | 9.0 | 405 | 0.4247 | 0.8534 | 0.7131 | 0.6305 | 0.6403 | 0.8419 |
70
+ | 0.3124 | 10.0 | 450 | 0.4419 | 0.8591 | 0.7675 | 0.6622 | 0.6852 | 0.8508 |
71
+ | 0.3124 | 11.0 | 495 | 0.4351 | 0.8566 | 0.7533 | 0.6746 | 0.6953 | 0.8502 |
72
+ | 0.2778 | 12.0 | 540 | 0.4418 | 0.8579 | 0.7673 | 0.6778 | 0.7026 | 0.8514 |
73
+ | 0.2572 | 13.0 | 585 | 0.5176 | 0.8497 | 0.7386 | 0.6759 | 0.6962 | 0.8443 |
74
+ | 0.2252 | 14.0 | 630 | 0.4637 | 0.8503 | 0.7174 | 0.6935 | 0.7034 | 0.8479 |
75
+ | 0.2127 | 15.0 | 675 | 0.5122 | 0.8509 | 0.7916 | 0.6596 | 0.6877 | 0.8424 |
76
+ | 0.1798 | 16.0 | 720 | 0.5424 | 0.8433 | 0.7153 | 0.6577 | 0.6757 | 0.8369 |
77
+ | 0.1483 | 17.0 | 765 | 0.5590 | 0.8522 | 0.7237 | 0.6779 | 0.6940 | 0.8475 |
78
+ | 0.1414 | 18.0 | 810 | 0.6393 | 0.8610 | 0.7674 | 0.6679 | 0.6913 | 0.8532 |
79
+ | 0.1173 | 19.0 | 855 | 0.6078 | 0.8465 | 0.7128 | 0.6905 | 0.7000 | 0.8442 |
80
+ | 0.1019 | 20.0 | 900 | 0.6100 | 0.8547 | 0.7817 | 0.6473 | 0.6684 | 0.8444 |
81
+ | 0.1019 | 21.0 | 945 | 0.7196 | 0.8515 | 0.7398 | 0.6640 | 0.6854 | 0.8445 |
82
+ | 0.0913 | 22.0 | 990 | 0.7781 | 0.8332 | 0.6793 | 0.6502 | 0.6608 | 0.8285 |
83
+ | 0.0764 | 23.0 | 1035 | 0.7152 | 0.8522 | 0.7098 | 0.6866 | 0.6960 | 0.8494 |
84
+ | 0.0656 | 24.0 | 1080 | 0.7987 | 0.8446 | 0.6926 | 0.6917 | 0.6918 | 0.8444 |
85
+ | 0.0613 | 25.0 | 1125 | 0.7605 | 0.8572 | 0.7165 | 0.6988 | 0.7063 | 0.8551 |
86
+ | 0.0527 | 26.0 | 1170 | 0.7406 | 0.8572 | 0.7322 | 0.6900 | 0.7056 | 0.8532 |
87
+ | 0.0432 | 27.0 | 1215 | 0.8191 | 0.8572 | 0.7354 | 0.6893 | 0.7062 | 0.8530 |
88
+ | 0.038 | 28.0 | 1260 | 0.7626 | 0.8598 | 0.7403 | 0.6714 | 0.6908 | 0.8531 |
89
+ | 0.0354 | 29.0 | 1305 | 0.8406 | 0.8553 | 0.7084 | 0.6848 | 0.6942 | 0.8523 |
90
+ | 0.0298 | 30.0 | 1350 | 0.8857 | 0.8490 | 0.7100 | 0.6873 | 0.6969 | 0.8464 |
91
+ | 0.0298 | 31.0 | 1395 | 0.8856 | 0.8553 | 0.7516 | 0.6753 | 0.6981 | 0.8491 |
92
+ | 0.0243 | 32.0 | 1440 | 0.8640 | 0.8623 | 0.7457 | 0.7018 | 0.7184 | 0.8586 |
93
+ | 0.0256 | 33.0 | 1485 | 0.8976 | 0.8515 | 0.7116 | 0.6892 | 0.6987 | 0.8490 |
94
+ | 0.0189 | 34.0 | 1530 | 0.8932 | 0.8579 | 0.7306 | 0.6822 | 0.6988 | 0.8530 |
95
+ | 0.0172 | 35.0 | 1575 | 0.9222 | 0.8497 | 0.6978 | 0.6842 | 0.6902 | 0.8478 |
96
+ | 0.0146 | 36.0 | 1620 | 0.9238 | 0.8579 | 0.7263 | 0.6860 | 0.7009 | 0.8537 |
97
+ | 0.0148 | 37.0 | 1665 | 0.9424 | 0.8528 | 0.7068 | 0.6862 | 0.6950 | 0.8502 |
98
+ | 0.0129 | 38.0 | 1710 | 0.9515 | 0.8522 | 0.7128 | 0.6815 | 0.6938 | 0.8485 |
99
+ | 0.0106 | 39.0 | 1755 | 0.9490 | 0.8528 | 0.7155 | 0.6820 | 0.6950 | 0.8490 |
100
+ | 0.0136 | 40.0 | 1800 | 0.9484 | 0.8522 | 0.7150 | 0.6816 | 0.6946 | 0.8484 |
101
+
102
+
103
+ ### Framework versions
104
+
105
+ - Transformers 4.55.0
106
+ - Pytorch 2.7.0+cu126
107
+ - Datasets 4.0.0
108
+ - Tokenizers 0.21.4
classification_report_test.txt ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ precision recall f1-score support
2
+
3
+ negative 0.81 0.89 0.85 1409
4
+ neutral 0.49 0.25 0.33 167
5
+ positive 0.89 0.85 0.87 1590
6
+
7
+ accuracy 0.84 3166
8
+ macro avg 0.73 0.66 0.68 3166
9
+ weighted avg 0.83 0.84 0.83 3166
10
+
11
+ Confusion matrix:
12
+ [[1261 21 127]
13
+ [ 79 41 47]
14
+ [ 213 22 1355]]
confusion_matrix_test.csv ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ ,negative,neutral,positive
2
+ negative,1261,21,127
3
+ neutral,79,41,47
4
+ positive,213,22,1355
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:15d231ba7df8b1fcc2d357ff3da44d7f10e435264694abf0d8519ff75c56d4a5
3
  size 498615900
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:61c4d9163afb0625a9efb396a3c27b58869cd32d34575139d74f8005946fec56
3
  size 498615900
model_predict.csv ADDED
The diff for this file is too large to render. See raw diff