update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,96 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: mit
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
model-index:
|
6 |
+
- name: predict-perception-xlmr-blame-concept
|
7 |
+
results: []
|
8 |
+
---
|
9 |
+
|
10 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
11 |
+
should probably proofread and complete it, then remove this comment. -->
|
12 |
+
|
13 |
+
# predict-perception-xlmr-blame-concept
|
14 |
+
|
15 |
+
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
|
16 |
+
It achieves the following results on the evaluation set:
|
17 |
+
- Loss: 0.9414
|
18 |
+
- Rmse: 0.7875
|
19 |
+
- Rmse Blame::a Un concetto astratto o un'emozione: 0.7875
|
20 |
+
- Mae: 0.6165
|
21 |
+
- Mae Blame::a Un concetto astratto o un'emozione: 0.6165
|
22 |
+
- R2: 0.2291
|
23 |
+
- R2 Blame::a Un concetto astratto o un'emozione: 0.2291
|
24 |
+
- Cos: 0.1304
|
25 |
+
- Pair: 0.0
|
26 |
+
- Rank: 0.5
|
27 |
+
- Neighbors: 0.3509
|
28 |
+
- Rsa: nan
|
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: 1e-05
|
48 |
+
- train_batch_size: 20
|
49 |
+
- eval_batch_size: 8
|
50 |
+
- seed: 1996
|
51 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
52 |
+
- lr_scheduler_type: linear
|
53 |
+
- num_epochs: 30
|
54 |
+
|
55 |
+
### Training results
|
56 |
+
|
57 |
+
| Training Loss | Epoch | Step | Validation Loss | Rmse | Rmse Blame::a Un concetto astratto o un'emozione | Mae | Mae Blame::a Un concetto astratto o un'emozione | R2 | R2 Blame::a Un concetto astratto o un'emozione | Cos | Pair | Rank | Neighbors | Rsa |
|
58 |
+
|:-------------:|:-----:|:----:|:---------------:|:------:|:------------------------------------------------:|:------:|:-----------------------------------------------:|:------:|:----------------------------------------------:|:-------:|:----:|:----:|:---------:|:---:|
|
59 |
+
| 1.0549 | 1.0 | 15 | 1.2093 | 0.8925 | 0.8925 | 0.6659 | 0.6659 | 0.0097 | 0.0097 | -0.3043 | 0.0 | 0.5 | 0.4013 | nan |
|
60 |
+
| 1.0085 | 2.0 | 30 | 1.2199 | 0.8964 | 0.8964 | 0.6494 | 0.6494 | 0.0010 | 0.0010 | -0.1304 | 0.0 | 0.5 | 0.4515 | nan |
|
61 |
+
| 1.0131 | 3.0 | 45 | 1.1798 | 0.8815 | 0.8815 | 0.6412 | 0.6412 | 0.0339 | 0.0339 | -0.2174 | 0.0 | 0.5 | 0.2402 | nan |
|
62 |
+
| 0.9931 | 4.0 | 60 | 1.1726 | 0.8788 | 0.8788 | 0.6370 | 0.6370 | 0.0397 | 0.0397 | -0.1304 | 0.0 | 0.5 | 0.2911 | nan |
|
63 |
+
| 0.9668 | 5.0 | 75 | 1.1194 | 0.8587 | 0.8587 | 0.5925 | 0.5925 | 0.0833 | 0.0833 | 0.2174 | 0.0 | 0.5 | 0.3303 | nan |
|
64 |
+
| 0.8759 | 6.0 | 90 | 1.0776 | 0.8425 | 0.8425 | 0.6265 | 0.6265 | 0.1175 | 0.1175 | 0.3043 | 0.0 | 0.5 | 0.4190 | nan |
|
65 |
+
| 0.8787 | 7.0 | 105 | 1.0513 | 0.8321 | 0.8321 | 0.6087 | 0.6087 | 0.1391 | 0.1391 | 0.2174 | 0.0 | 0.5 | 0.3303 | nan |
|
66 |
+
| 0.7637 | 8.0 | 120 | 1.0537 | 0.8331 | 0.8331 | 0.6265 | 0.6265 | 0.1372 | 0.1372 | 0.2174 | 0.0 | 0.5 | 0.3303 | nan |
|
67 |
+
| 0.6568 | 9.0 | 135 | 0.9104 | 0.7744 | 0.7744 | 0.5887 | 0.5887 | 0.2544 | 0.2544 | 0.3043 | 0.0 | 0.5 | 0.3680 | nan |
|
68 |
+
| 0.6354 | 10.0 | 150 | 0.9055 | 0.7723 | 0.7723 | 0.6222 | 0.6222 | 0.2585 | 0.2585 | 0.1304 | 0.0 | 0.5 | 0.3987 | nan |
|
69 |
+
| 0.5107 | 11.0 | 165 | 1.0173 | 0.8186 | 0.8186 | 0.6168 | 0.6168 | 0.1669 | 0.1669 | 0.2174 | 0.0 | 0.5 | 0.3303 | nan |
|
70 |
+
| 0.4598 | 12.0 | 180 | 0.9155 | 0.7765 | 0.7765 | 0.6284 | 0.6284 | 0.2503 | 0.2503 | 0.1304 | 0.0 | 0.5 | 0.3987 | nan |
|
71 |
+
| 0.3815 | 13.0 | 195 | 0.9255 | 0.7808 | 0.7808 | 0.6140 | 0.6140 | 0.2421 | 0.2421 | 0.1304 | 0.0 | 0.5 | 0.3987 | nan |
|
72 |
+
| 0.3303 | 14.0 | 210 | 0.8506 | 0.7485 | 0.7485 | 0.6076 | 0.6076 | 0.3035 | 0.3035 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
73 |
+
| 0.2799 | 15.0 | 225 | 1.0272 | 0.8226 | 0.8226 | 0.6699 | 0.6699 | 0.1588 | 0.1588 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
74 |
+
| 0.2998 | 16.0 | 240 | 0.9969 | 0.8103 | 0.8103 | 0.6461 | 0.6461 | 0.1836 | 0.1836 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
75 |
+
| 0.3131 | 17.0 | 255 | 0.9066 | 0.7727 | 0.7727 | 0.5849 | 0.5849 | 0.2576 | 0.2576 | 0.2174 | 0.0 | 0.5 | 0.3303 | nan |
|
76 |
+
| 0.2234 | 18.0 | 270 | 0.8741 | 0.7588 | 0.7588 | 0.5953 | 0.5953 | 0.2842 | 0.2842 | 0.2174 | 0.0 | 0.5 | 0.3303 | nan |
|
77 |
+
| 0.2481 | 19.0 | 285 | 1.0022 | 0.8125 | 0.8125 | 0.6549 | 0.6549 | 0.1793 | 0.1793 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
78 |
+
| 0.2333 | 20.0 | 300 | 0.9238 | 0.7801 | 0.7801 | 0.6180 | 0.6180 | 0.2435 | 0.2435 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
79 |
+
| 0.2407 | 21.0 | 315 | 0.9868 | 0.8062 | 0.8062 | 0.6457 | 0.6457 | 0.1919 | 0.1919 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
80 |
+
| 0.2122 | 22.0 | 330 | 0.9514 | 0.7916 | 0.7916 | 0.6204 | 0.6204 | 0.2209 | 0.2209 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
81 |
+
| 0.2162 | 23.0 | 345 | 0.9227 | 0.7796 | 0.7796 | 0.6053 | 0.6053 | 0.2444 | 0.2444 | 0.1304 | 0.0 | 0.5 | 0.3509 | nan |
|
82 |
+
| 0.1739 | 24.0 | 360 | 0.9147 | 0.7762 | 0.7762 | 0.5979 | 0.5979 | 0.2510 | 0.2510 | 0.1304 | 0.0 | 0.5 | 0.3509 | nan |
|
83 |
+
| 0.2084 | 25.0 | 375 | 0.9645 | 0.7970 | 0.7970 | 0.6296 | 0.6296 | 0.2102 | 0.2102 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
84 |
+
| 0.1702 | 26.0 | 390 | 0.9587 | 0.7946 | 0.7946 | 0.6279 | 0.6279 | 0.2149 | 0.2149 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
85 |
+
| 0.2146 | 27.0 | 405 | 0.9519 | 0.7918 | 0.7918 | 0.6273 | 0.6273 | 0.2205 | 0.2205 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
86 |
+
| 0.1645 | 28.0 | 420 | 0.9398 | 0.7868 | 0.7868 | 0.6181 | 0.6181 | 0.2304 | 0.2304 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
87 |
+
| 0.2052 | 29.0 | 435 | 0.9492 | 0.7907 | 0.7907 | 0.6228 | 0.6228 | 0.2227 | 0.2227 | 0.0435 | 0.0 | 0.5 | 0.2862 | nan |
|
88 |
+
| 0.147 | 30.0 | 450 | 0.9414 | 0.7875 | 0.7875 | 0.6165 | 0.6165 | 0.2291 | 0.2291 | 0.1304 | 0.0 | 0.5 | 0.3509 | nan |
|
89 |
+
|
90 |
+
|
91 |
+
### Framework versions
|
92 |
+
|
93 |
+
- Transformers 4.16.2
|
94 |
+
- Pytorch 1.10.2+cu113
|
95 |
+
- Datasets 1.18.3
|
96 |
+
- Tokenizers 0.11.0
|