update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,136 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: mit
|
3 |
+
base_model: roberta-base
|
4 |
+
tags:
|
5 |
+
- generated_from_trainer
|
6 |
+
metrics:
|
7 |
+
- accuracy
|
8 |
+
model-index:
|
9 |
+
- name: roberta-base-sst-2-16-13-smoothed
|
10 |
+
results: []
|
11 |
+
---
|
12 |
+
|
13 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
14 |
+
should probably proofread and complete it, then remove this comment. -->
|
15 |
+
|
16 |
+
# roberta-base-sst-2-16-13-smoothed
|
17 |
+
|
18 |
+
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
|
19 |
+
It achieves the following results on the evaluation set:
|
20 |
+
- Loss: 0.5750
|
21 |
+
- Accuracy: 0.9688
|
22 |
+
|
23 |
+
## Model description
|
24 |
+
|
25 |
+
More information needed
|
26 |
+
|
27 |
+
## Intended uses & limitations
|
28 |
+
|
29 |
+
More information needed
|
30 |
+
|
31 |
+
## Training and evaluation data
|
32 |
+
|
33 |
+
More information needed
|
34 |
+
|
35 |
+
## Training procedure
|
36 |
+
|
37 |
+
### Training hyperparameters
|
38 |
+
|
39 |
+
The following hyperparameters were used during training:
|
40 |
+
- learning_rate: 1e-05
|
41 |
+
- train_batch_size: 32
|
42 |
+
- eval_batch_size: 32
|
43 |
+
- seed: 42
|
44 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
45 |
+
- lr_scheduler_type: linear
|
46 |
+
- lr_scheduler_warmup_steps: 50
|
47 |
+
- num_epochs: 75
|
48 |
+
- label_smoothing_factor: 0.45
|
49 |
+
|
50 |
+
### Training results
|
51 |
+
|
52 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
53 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
54 |
+
| No log | 1.0 | 1 | 0.6919 | 0.5 |
|
55 |
+
| No log | 2.0 | 2 | 0.6919 | 0.5 |
|
56 |
+
| No log | 3.0 | 3 | 0.6919 | 0.5 |
|
57 |
+
| No log | 4.0 | 4 | 0.6919 | 0.5 |
|
58 |
+
| No log | 5.0 | 5 | 0.6919 | 0.5 |
|
59 |
+
| No log | 6.0 | 6 | 0.6918 | 0.5 |
|
60 |
+
| No log | 7.0 | 7 | 0.6918 | 0.5 |
|
61 |
+
| No log | 8.0 | 8 | 0.6918 | 0.5 |
|
62 |
+
| No log | 9.0 | 9 | 0.6918 | 0.5 |
|
63 |
+
| 0.6949 | 10.0 | 10 | 0.6917 | 0.5 |
|
64 |
+
| 0.6949 | 11.0 | 11 | 0.6917 | 0.5 |
|
65 |
+
| 0.6949 | 12.0 | 12 | 0.6916 | 0.5 |
|
66 |
+
| 0.6949 | 13.0 | 13 | 0.6916 | 0.5 |
|
67 |
+
| 0.6949 | 14.0 | 14 | 0.6915 | 0.5 |
|
68 |
+
| 0.6949 | 15.0 | 15 | 0.6914 | 0.5 |
|
69 |
+
| 0.6949 | 16.0 | 16 | 0.6914 | 0.5312 |
|
70 |
+
| 0.6949 | 17.0 | 17 | 0.6913 | 0.5312 |
|
71 |
+
| 0.6949 | 18.0 | 18 | 0.6912 | 0.5312 |
|
72 |
+
| 0.6949 | 19.0 | 19 | 0.6911 | 0.625 |
|
73 |
+
| 0.6926 | 20.0 | 20 | 0.6910 | 0.625 |
|
74 |
+
| 0.6926 | 21.0 | 21 | 0.6909 | 0.6562 |
|
75 |
+
| 0.6926 | 22.0 | 22 | 0.6907 | 0.6875 |
|
76 |
+
| 0.6926 | 23.0 | 23 | 0.6906 | 0.6875 |
|
77 |
+
| 0.6926 | 24.0 | 24 | 0.6904 | 0.6875 |
|
78 |
+
| 0.6926 | 25.0 | 25 | 0.6902 | 0.75 |
|
79 |
+
| 0.6926 | 26.0 | 26 | 0.6899 | 0.75 |
|
80 |
+
| 0.6926 | 27.0 | 27 | 0.6896 | 0.75 |
|
81 |
+
| 0.6926 | 28.0 | 28 | 0.6893 | 0.7188 |
|
82 |
+
| 0.6926 | 29.0 | 29 | 0.6890 | 0.6875 |
|
83 |
+
| 0.687 | 30.0 | 30 | 0.6885 | 0.6875 |
|
84 |
+
| 0.687 | 31.0 | 31 | 0.6880 | 0.7188 |
|
85 |
+
| 0.687 | 32.0 | 32 | 0.6874 | 0.7188 |
|
86 |
+
| 0.687 | 33.0 | 33 | 0.6866 | 0.7188 |
|
87 |
+
| 0.687 | 34.0 | 34 | 0.6857 | 0.7188 |
|
88 |
+
| 0.687 | 35.0 | 35 | 0.6846 | 0.75 |
|
89 |
+
| 0.687 | 36.0 | 36 | 0.6832 | 0.75 |
|
90 |
+
| 0.687 | 37.0 | 37 | 0.6814 | 0.7812 |
|
91 |
+
| 0.687 | 38.0 | 38 | 0.6791 | 0.7812 |
|
92 |
+
| 0.687 | 39.0 | 39 | 0.6761 | 0.875 |
|
93 |
+
| 0.6732 | 40.0 | 40 | 0.6721 | 0.9062 |
|
94 |
+
| 0.6732 | 41.0 | 41 | 0.6670 | 0.9062 |
|
95 |
+
| 0.6732 | 42.0 | 42 | 0.6601 | 0.9062 |
|
96 |
+
| 0.6732 | 43.0 | 43 | 0.6510 | 0.875 |
|
97 |
+
| 0.6732 | 44.0 | 44 | 0.6392 | 0.875 |
|
98 |
+
| 0.6732 | 45.0 | 45 | 0.6248 | 0.875 |
|
99 |
+
| 0.6732 | 46.0 | 46 | 0.6098 | 0.875 |
|
100 |
+
| 0.6732 | 47.0 | 47 | 0.5961 | 0.875 |
|
101 |
+
| 0.6732 | 48.0 | 48 | 0.5884 | 0.9375 |
|
102 |
+
| 0.6732 | 49.0 | 49 | 0.5833 | 0.9375 |
|
103 |
+
| 0.5913 | 50.0 | 50 | 0.5795 | 0.9062 |
|
104 |
+
| 0.5913 | 51.0 | 51 | 0.5851 | 0.9062 |
|
105 |
+
| 0.5913 | 52.0 | 52 | 0.5985 | 0.875 |
|
106 |
+
| 0.5913 | 53.0 | 53 | 0.6110 | 0.8125 |
|
107 |
+
| 0.5913 | 54.0 | 54 | 0.6092 | 0.8438 |
|
108 |
+
| 0.5913 | 55.0 | 55 | 0.6007 | 0.8438 |
|
109 |
+
| 0.5913 | 56.0 | 56 | 0.5904 | 0.875 |
|
110 |
+
| 0.5913 | 57.0 | 57 | 0.5846 | 0.9062 |
|
111 |
+
| 0.5913 | 58.0 | 58 | 0.5829 | 0.9062 |
|
112 |
+
| 0.5913 | 59.0 | 59 | 0.5843 | 0.9062 |
|
113 |
+
| 0.544 | 60.0 | 60 | 0.5900 | 0.8438 |
|
114 |
+
| 0.544 | 61.0 | 61 | 0.5970 | 0.8438 |
|
115 |
+
| 0.544 | 62.0 | 62 | 0.6026 | 0.8438 |
|
116 |
+
| 0.544 | 63.0 | 63 | 0.6030 | 0.8438 |
|
117 |
+
| 0.544 | 64.0 | 64 | 0.5980 | 0.8438 |
|
118 |
+
| 0.544 | 65.0 | 65 | 0.5901 | 0.8438 |
|
119 |
+
| 0.544 | 66.0 | 66 | 0.5843 | 0.875 |
|
120 |
+
| 0.544 | 67.0 | 67 | 0.5800 | 0.9062 |
|
121 |
+
| 0.544 | 68.0 | 68 | 0.5779 | 0.9375 |
|
122 |
+
| 0.544 | 69.0 | 69 | 0.5765 | 0.9375 |
|
123 |
+
| 0.5383 | 70.0 | 70 | 0.5758 | 0.9688 |
|
124 |
+
| 0.5383 | 71.0 | 71 | 0.5754 | 0.9688 |
|
125 |
+
| 0.5383 | 72.0 | 72 | 0.5752 | 0.9688 |
|
126 |
+
| 0.5383 | 73.0 | 73 | 0.5751 | 0.9688 |
|
127 |
+
| 0.5383 | 74.0 | 74 | 0.5750 | 0.9688 |
|
128 |
+
| 0.5383 | 75.0 | 75 | 0.5750 | 0.9688 |
|
129 |
+
|
130 |
+
|
131 |
+
### Framework versions
|
132 |
+
|
133 |
+
- Transformers 4.32.0.dev0
|
134 |
+
- Pytorch 2.0.1+cu118
|
135 |
+
- Datasets 2.4.0
|
136 |
+
- Tokenizers 0.13.3
|