Model save
Browse files- README.md +87 -0
- classification_report_test.txt +14 -0
- confusion_matrix_test.csv +4 -0
- model.safetensors +1 -1
README.md
ADDED
@@ -0,0 +1,87 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: transformers
|
3 |
+
license: mit
|
4 |
+
base_model: nlptown/bert-base-multilingual-uncased-sentiment
|
5 |
+
tags:
|
6 |
+
- generated_from_trainer
|
7 |
+
metrics:
|
8 |
+
- accuracy
|
9 |
+
model-index:
|
10 |
+
- name: bert-base-multilingual-uncased-sentiment_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 |
+
# bert-base-multilingual-uncased-sentiment_v3
|
18 |
+
|
19 |
+
This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on an unknown dataset.
|
20 |
+
It achieves the following results on the evaluation set:
|
21 |
+
- Loss: 0.4987
|
22 |
+
- Accuracy: 0.9286
|
23 |
+
- Precision Macro: 0.8226
|
24 |
+
- Recall Macro: 0.7931
|
25 |
+
- F1 Macro: 0.8061
|
26 |
+
- F1 Weighted: 0.9269
|
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: 64
|
47 |
+
- eval_batch_size: 64
|
48 |
+
- seed: 42
|
49 |
+
- gradient_accumulation_steps: 2
|
50 |
+
- total_train_batch_size: 128
|
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 |
+
| 0.3933 | 1.0 | 90 | 0.2349 | 0.9292 | 0.8484 | 0.7197 | 0.7474 | 0.9202 |
|
61 |
+
| 0.2051 | 2.0 | 180 | 0.2166 | 0.9236 | 0.8134 | 0.7619 | 0.7811 | 0.9199 |
|
62 |
+
| 0.1494 | 3.0 | 270 | 0.2369 | 0.9362 | 0.8619 | 0.7775 | 0.8072 | 0.9321 |
|
63 |
+
| 0.1233 | 4.0 | 360 | 0.2290 | 0.9343 | 0.8660 | 0.7894 | 0.8176 | 0.9309 |
|
64 |
+
| 0.0838 | 5.0 | 450 | 0.2490 | 0.9375 | 0.8610 | 0.8200 | 0.8378 | 0.9358 |
|
65 |
+
| 0.0799 | 6.0 | 540 | 0.2579 | 0.9343 | 0.8528 | 0.7977 | 0.8197 | 0.9317 |
|
66 |
+
| 0.0481 | 7.0 | 630 | 0.3494 | 0.9223 | 0.7926 | 0.8252 | 0.8064 | 0.9247 |
|
67 |
+
| 0.0406 | 8.0 | 720 | 0.3154 | 0.9368 | 0.8591 | 0.7986 | 0.8227 | 0.9341 |
|
68 |
+
| 0.032 | 9.0 | 810 | 0.3219 | 0.9305 | 0.8238 | 0.8153 | 0.8194 | 0.9301 |
|
69 |
+
| 0.0333 | 10.0 | 900 | 0.3787 | 0.9286 | 0.8387 | 0.8048 | 0.8198 | 0.9270 |
|
70 |
+
| 0.0278 | 11.0 | 990 | 0.3914 | 0.9311 | 0.8432 | 0.7948 | 0.8148 | 0.9288 |
|
71 |
+
| 0.0165 | 12.0 | 1080 | 0.4155 | 0.9318 | 0.8627 | 0.7830 | 0.8120 | 0.9282 |
|
72 |
+
| 0.0126 | 13.0 | 1170 | 0.4029 | 0.9368 | 0.8550 | 0.8161 | 0.8328 | 0.9352 |
|
73 |
+
| 0.0133 | 14.0 | 1260 | 0.4398 | 0.9324 | 0.8460 | 0.7915 | 0.8134 | 0.9297 |
|
74 |
+
| 0.01 | 15.0 | 1350 | 0.4571 | 0.9318 | 0.8347 | 0.7913 | 0.8094 | 0.9294 |
|
75 |
+
| 0.008 | 16.0 | 1440 | 0.4685 | 0.9299 | 0.8303 | 0.7899 | 0.8070 | 0.9276 |
|
76 |
+
| 0.0058 | 17.0 | 1530 | 0.4846 | 0.9318 | 0.8403 | 0.7954 | 0.8142 | 0.9295 |
|
77 |
+
| 0.0022 | 18.0 | 1620 | 0.4905 | 0.9280 | 0.8249 | 0.7928 | 0.8068 | 0.9262 |
|
78 |
+
| 0.0038 | 19.0 | 1710 | 0.5043 | 0.9299 | 0.8272 | 0.7897 | 0.8057 | 0.9277 |
|
79 |
+
| 0.0015 | 20.0 | 1800 | 0.4987 | 0.9286 | 0.8226 | 0.7931 | 0.8061 | 0.9269 |
|
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 0.91 0.95 0.93 1409
|
4 |
+
neutral 0.57 0.39 0.46 167
|
5 |
+
positive 0.94 0.93 0.94 1590
|
6 |
+
|
7 |
+
accuracy 0.91 3166
|
8 |
+
macro avg 0.80 0.76 0.78 3166
|
9 |
+
weighted avg 0.91 0.91 0.91 3166
|
10 |
+
|
11 |
+
Confusion matrix:
|
12 |
+
[[1339 23 47]
|
13 |
+
[ 51 65 51]
|
14 |
+
[ 79 27 1484]]
|
confusion_matrix_test.csv
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
,negative,neutral,positive
|
2 |
+
negative,1339,23,47
|
3 |
+
neutral,51,65,51
|
4 |
+
positive,79,27,1484
|
model.safetensors
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 669458436
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:81a404a4d6ea0bad2f2f56dd2fc62eac8f49ed4d93f0e2536278cd5ec2360986
|
3 |
size 669458436
|