dariuslimzh
commited on
Commit
•
fd08622
1
Parent(s):
6cbf0ab
Training completed
Browse files
README.md
ADDED
@@ -0,0 +1,72 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
base_model: ICT2214Team7/RoBERTa_Test_Training
|
4 |
+
tags:
|
5 |
+
- generated_from_trainer
|
6 |
+
metrics:
|
7 |
+
- precision
|
8 |
+
- recall
|
9 |
+
- f1
|
10 |
+
- accuracy
|
11 |
+
model-index:
|
12 |
+
- name: RoBERTa_Combined_Generated_v1.1_epoch_6
|
13 |
+
results: []
|
14 |
+
---
|
15 |
+
|
16 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
17 |
+
should probably proofread and complete it, then remove this comment. -->
|
18 |
+
|
19 |
+
# RoBERTa_Combined_Generated_v1.1_epoch_6
|
20 |
+
|
21 |
+
This model is a fine-tuned version of [ICT2214Team7/RoBERTa_Test_Training](https://huggingface.co/ICT2214Team7/RoBERTa_Test_Training) on an unknown dataset.
|
22 |
+
It achieves the following results on the evaluation set:
|
23 |
+
- Loss: 0.0004
|
24 |
+
- Precision: 0.9980
|
25 |
+
- Recall: 0.9980
|
26 |
+
- F1: 0.9980
|
27 |
+
- Accuracy: 0.9996
|
28 |
+
- Report: {'AGE': {'precision': 1.0, 'recall': 0.9444444444444444, 'f1-score': 0.9714285714285714, 'support': 18}, 'LOC': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 101}, 'NAT': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 25}, 'ORG': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 173}, 'PER': {'precision': 0.9943502824858758, 'recall': 1.0, 'f1-score': 0.9971671388101983, 'support': 176}, 'micro avg': {'precision': 0.9979716024340771, 'recall': 0.9979716024340771, 'f1-score': 0.9979716024340771, 'support': 493}, 'macro avg': {'precision': 0.9988700564971751, 'recall': 0.9888888888888889, 'f1-score': 0.9937191420477539, 'support': 493}, 'weighted avg': {'precision': 0.9979830623073309, 'recall': 0.9979716024340771, 'f1-score': 0.9979454984103634, 'support': 493}}
|
29 |
+
|
30 |
+
## Model description
|
31 |
+
|
32 |
+
More information needed
|
33 |
+
|
34 |
+
## Intended uses & limitations
|
35 |
+
|
36 |
+
More information needed
|
37 |
+
|
38 |
+
## Training and evaluation data
|
39 |
+
|
40 |
+
More information needed
|
41 |
+
|
42 |
+
## Training procedure
|
43 |
+
|
44 |
+
### Training hyperparameters
|
45 |
+
|
46 |
+
The following hyperparameters were used during training:
|
47 |
+
- learning_rate: 5e-05
|
48 |
+
- train_batch_size: 8
|
49 |
+
- eval_batch_size: 8
|
50 |
+
- seed: 42
|
51 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
52 |
+
- lr_scheduler_type: linear
|
53 |
+
- num_epochs: 6
|
54 |
+
|
55 |
+
### Training results
|
56 |
+
|
57 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Report |
|
58 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
|
59 |
+
| No log | 1.0 | 200 | 0.0074 | 0.9799 | 0.9899 | 0.9849 | 0.9980 | {'AGE': {'precision': 1.0, 'recall': 0.9444444444444444, 'f1-score': 0.9714285714285714, 'support': 18}, 'LOC': {'precision': 0.9801980198019802, 'recall': 0.9801980198019802, 'f1-score': 0.9801980198019802, 'support': 101}, 'NAT': {'precision': 1.0, 'recall': 0.96, 'f1-score': 0.9795918367346939, 'support': 25}, 'ORG': {'precision': 0.9774011299435028, 'recall': 1.0, 'f1-score': 0.9885714285714285, 'support': 173}, 'PER': {'precision': 0.9776536312849162, 'recall': 0.9943181818181818, 'f1-score': 0.9859154929577464, 'support': 176}, 'micro avg': {'precision': 0.9799196787148594, 'recall': 0.9898580121703854, 'f1-score': 0.9848637739656912, 'support': 493}, 'macro avg': {'precision': 0.9870505562060797, 'recall': 0.9757921292129212, 'f1-score': 0.981141069898884, 'support': 493}, 'weighted avg': {'precision': 0.9800353642725582, 'recall': 0.9898580121703854, 'f1-score': 0.9848265600557851, 'support': 493}} |
|
60 |
+
| No log | 2.0 | 400 | 0.0019 | 0.9959 | 0.9959 | 0.9959 | 0.9995 | {'AGE': {'precision': 1.0, 'recall': 0.9444444444444444, 'f1-score': 0.9714285714285714, 'support': 18}, 'LOC': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 101}, 'NAT': {'precision': 1.0, 'recall': 0.96, 'f1-score': 0.9795918367346939, 'support': 25}, 'ORG': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 173}, 'PER': {'precision': 0.9887640449438202, 'recall': 1.0, 'f1-score': 0.9943502824858756, 'support': 176}, 'micro avg': {'precision': 0.9959432048681541, 'recall': 0.9959432048681541, 'f1-score': 0.9959432048681541, 'support': 493}, 'macro avg': {'precision': 0.997752808988764, 'recall': 0.9808888888888889, 'f1-score': 0.9890741381298283, 'support': 493}, 'weighted avg': {'precision': 0.9959887868359277, 'recall': 0.9959432048681541, 'f1-score': 0.995904989698977, 'support': 493}} |
|
61 |
+
| 0.0654 | 3.0 | 600 | 0.0015 | 0.9959 | 0.9959 | 0.9959 | 0.9995 | {'AGE': {'precision': 1.0, 'recall': 0.9444444444444444, 'f1-score': 0.9714285714285714, 'support': 18}, 'LOC': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 101}, 'NAT': {'precision': 1.0, 'recall': 0.96, 'f1-score': 0.9795918367346939, 'support': 25}, 'ORG': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 173}, 'PER': {'precision': 0.9887640449438202, 'recall': 1.0, 'f1-score': 0.9943502824858756, 'support': 176}, 'micro avg': {'precision': 0.9959432048681541, 'recall': 0.9959432048681541, 'f1-score': 0.9959432048681541, 'support': 493}, 'macro avg': {'precision': 0.997752808988764, 'recall': 0.9808888888888889, 'f1-score': 0.9890741381298283, 'support': 493}, 'weighted avg': {'precision': 0.9959887868359277, 'recall': 0.9959432048681541, 'f1-score': 0.995904989698977, 'support': 493}} |
|
62 |
+
| 0.0654 | 4.0 | 800 | 0.0007 | 0.9919 | 0.9959 | 0.9939 | 0.9996 | {'AGE': {'precision': 0.8947368421052632, 'recall': 0.9444444444444444, 'f1-score': 0.918918918918919, 'support': 18}, 'LOC': {'precision': 0.9900990099009901, 'recall': 0.9900990099009901, 'f1-score': 0.9900990099009901, 'support': 101}, 'NAT': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 25}, 'ORG': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 173}, 'PER': {'precision': 0.9943502824858758, 'recall': 1.0, 'f1-score': 0.9971671388101983, 'support': 176}, 'micro avg': {'precision': 0.9919191919191919, 'recall': 0.9959432048681541, 'f1-score': 0.9939271255060729, 'support': 493}, 'macro avg': {'precision': 0.9758372268984259, 'recall': 0.986908690869087, 'f1-score': 0.9812370135260216, 'support': 493}, 'weighted avg': {'precision': 0.9921113851428172, 'recall': 0.9959432048681541, 'f1-score': 0.9939999127203558, 'support': 493}} |
|
63 |
+
| 0.0026 | 5.0 | 1000 | 0.0005 | 0.9960 | 0.9980 | 0.9970 | 0.9998 | {'AGE': {'precision': 0.9444444444444444, 'recall': 0.9444444444444444, 'f1-score': 0.9444444444444444, 'support': 18}, 'LOC': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 101}, 'NAT': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 25}, 'ORG': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 173}, 'PER': {'precision': 0.9943502824858758, 'recall': 1.0, 'f1-score': 0.9971671388101983, 'support': 176}, 'micro avg': {'precision': 0.9959514170040485, 'recall': 0.9979716024340771, 'f1-score': 0.9969604863221885, 'support': 493}, 'macro avg': {'precision': 0.987758945386064, 'recall': 0.9888888888888889, 'f1-score': 0.9883223166509285, 'support': 493}, 'weighted avg': {'precision': 0.9959546647414079, 'recall': 0.9979716024340771, 'f1-score': 0.9969602767354866, 'support': 493}} |
|
64 |
+
| 0.0026 | 6.0 | 1200 | 0.0004 | 0.9980 | 0.9980 | 0.9980 | 0.9996 | {'AGE': {'precision': 1.0, 'recall': 0.9444444444444444, 'f1-score': 0.9714285714285714, 'support': 18}, 'LOC': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 101}, 'NAT': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 25}, 'ORG': {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 173}, 'PER': {'precision': 0.9943502824858758, 'recall': 1.0, 'f1-score': 0.9971671388101983, 'support': 176}, 'micro avg': {'precision': 0.9979716024340771, 'recall': 0.9979716024340771, 'f1-score': 0.9979716024340771, 'support': 493}, 'macro avg': {'precision': 0.9988700564971751, 'recall': 0.9888888888888889, 'f1-score': 0.9937191420477539, 'support': 493}, 'weighted avg': {'precision': 0.9979830623073309, 'recall': 0.9979716024340771, 'f1-score': 0.9979454984103634, 'support': 493}} |
|
65 |
+
|
66 |
+
|
67 |
+
### Framework versions
|
68 |
+
|
69 |
+
- Transformers 4.40.2
|
70 |
+
- Pytorch 2.3.0+cu121
|
71 |
+
- Datasets 2.19.1
|
72 |
+
- Tokenizers 0.19.1
|