Hugging Face's logo

xshubhamx
/
roberta-base

Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Model card Files
xet
 Metrics Community
xshubhamx commited on
Commit
f8a60fd
·
verified ·
1 Parent(s): e92118b

End of training

Browse files
Files changed (2) hide show
  1. README.md +32 -21
  2. runs/Apr13_22-36-59_8b05f59ca40c/events.out.tfevents.1713047820.8b05f59ca40c.34.14 +2 -2
README.md CHANGED
@@ -17,21 +17,21 @@ should probably proofread and complete it, then remove this comment. -->
17
 
18
  This model was trained from scratch on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
- - Loss: 0.9148
21
- - Accuracy: 0.8311
22
- - Precision: 0.8263
23
- - Recall: 0.8311
24
- - Precision Macro: 0.7516
25
- - Recall Macro: 0.7538
26
- - Macro Fpr: 0.0149
27
- - Weighted Fpr: 0.0143
28
- - Weighted Specificity: 0.9782
29
- - Macro Specificity: 0.9873
30
- - Weighted Sensitivity: 0.8311
31
- - Macro Sensitivity: 0.7538
32
- - F1 Micro: 0.8311
33
- - F1 Macro: 0.7515
34
- - F1 Weighted: 0.8282
35
 
36
  ## Model description
37
 
@@ -56,17 +56,28 @@ The following hyperparameters were used during training:
56
  - seed: 42
57
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
58
  - lr_scheduler_type: linear
59
- - num_epochs: 5
 
60
 
61
  ### Training results
62
 
63
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Precision Macro | Recall Macro | Macro Fpr | Weighted Fpr | Weighted Specificity | Macro Specificity | Weighted Sensitivity | Macro Sensitivity | F1 Micro | F1 Macro | F1 Weighted |
64
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
65
- | 1.2817 | 1.0 | 643 | 0.8444 | 0.7250 | 0.6869 | 0.7250 | 0.4513 | 0.5022 | 0.0278 | 0.0264 | 0.9613 | 0.9791 | 0.7250 | 0.5022 | 0.7250 | 0.4502 | 0.6978 |
66
- | 0.818 | 2.0 | 1286 | 0.7113 | 0.7885 | 0.7831 | 0.7885 | 0.6570 | 0.6252 | 0.0195 | 0.0188 | 0.9728 | 0.9841 | 0.7885 | 0.6252 | 0.7885 | 0.6024 | 0.7753 |
67
- | 0.6484 | 3.0 | 1929 | 0.7289 | 0.8172 | 0.8148 | 0.8172 | 0.7681 | 0.7395 | 0.0164 | 0.0157 | 0.9754 | 0.9862 | 0.8172 | 0.7395 | 0.8172 | 0.7432 | 0.8135 |
68
- | 0.3228 | 4.0 | 2572 | 0.8768 | 0.8218 | 0.8192 | 0.8218 | 0.7516 | 0.7437 | 0.0158 | 0.0152 | 0.9769 | 0.9866 | 0.8218 | 0.7437 | 0.8218 | 0.7436 | 0.8193 |
69
- | 0.2242 | 5.0 | 3215 | 0.9148 | 0.8311 | 0.8263 | 0.8311 | 0.7516 | 0.7538 | 0.0149 | 0.0143 | 0.9782 | 0.9873 | 0.8311 | 0.7538 | 0.8311 | 0.7515 | 0.8282 |
 
 
 
 
 
 
 
 
 
 
70
 
71
 
72
  ### Framework versions
 
17
 
18
  This model was trained from scratch on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 1.3313
21
+ - Accuracy: 0.6344
22
+ - Precision: 0.5926
23
+ - Recall: 0.6344
24
+ - Precision Macro: 0.3231
25
+ - Recall Macro: 0.3898
26
+ - Macro Fpr: 0.0398
27
+ - Weighted Fpr: 0.0395
28
+ - Weighted Specificity: 0.9525
29
+ - Macro Specificity: 0.9725
30
+ - Weighted Sensitivity: 0.6344
31
+ - Macro Sensitivity: 0.3898
32
+ - F1 Micro: 0.6344
33
+ - F1 Macro: 0.3416
34
+ - F1 Weighted: 0.6051
35
 
36
  ## Model description
37
 
 
56
  - seed: 42
57
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
58
  - lr_scheduler_type: linear
59
+ - num_epochs: 15
60
+ - mixed_precision_training: Native AMP
61
 
62
  ### Training results
63
 
64
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Precision Macro | Recall Macro | Macro Fpr | Weighted Fpr | Weighted Specificity | Macro Specificity | Weighted Sensitivity | Macro Sensitivity | F1 Micro | F1 Macro | F1 Weighted |
65
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
66
+ | 2.2214 | 1.0 | 643 | 2.1982 | 0.2455 | 0.0603 | 0.2455 | 0.0164 | 0.0667 | 0.0667 | 0.1800 | 0.7545 | 0.9333 | 0.2455 | 0.0667 | 0.2455 | 0.0263 | 0.0968 |
67
+ | 2.1462 | 2.0 | 1286 | 1.9635 | 0.3362 | 0.1591 | 0.3362 | 0.0531 | 0.1155 | 0.0909 | 0.1236 | 0.8494 | 0.9457 | 0.3362 | 0.1155 | 0.3362 | 0.0655 | 0.2010 |
68
+ | 1.995 | 3.0 | 1929 | 1.9322 | 0.3555 | 0.2341 | 0.3555 | 0.0926 | 0.1435 | 0.0954 | 0.1146 | 0.8912 | 0.9498 | 0.3555 | 0.1435 | 0.3555 | 0.0931 | 0.2542 |
69
+ | 1.8909 | 4.0 | 2572 | 1.8875 | 0.3788 | 0.2875 | 0.3788 | 0.1270 | 0.2191 | 0.0871 | 0.1049 | 0.9094 | 0.9525 | 0.3788 | 0.2191 | 0.3788 | 0.1450 | 0.2977 |
70
+ | 1.7621 | 5.0 | 3215 | 1.7169 | 0.4284 | 0.3747 | 0.4284 | 0.1820 | 0.2270 | 0.0743 | 0.0870 | 0.9092 | 0.9558 | 0.4284 | 0.2270 | 0.4284 | 0.1745 | 0.3594 |
71
+ | 1.6254 | 6.0 | 3858 | 1.8831 | 0.4500 | 0.3948 | 0.4500 | 0.1878 | 0.2545 | 0.0794 | 0.0803 | 0.9240 | 0.9583 | 0.4500 | 0.2545 | 0.4500 | 0.1859 | 0.3970 |
72
+ | 1.4139 | 7.0 | 4501 | 1.6625 | 0.4640 | 0.4516 | 0.4640 | 0.2328 | 0.2949 | 0.0717 | 0.0762 | 0.9379 | 0.9601 | 0.4640 | 0.2949 | 0.4640 | 0.2285 | 0.4298 |
73
+ | 1.2681 | 8.0 | 5144 | 1.4462 | 0.5383 | 0.5269 | 0.5383 | 0.2766 | 0.3381 | 0.0560 | 0.0577 | 0.9451 | 0.9656 | 0.5383 | 0.3381 | 0.5383 | 0.2703 | 0.4888 |
74
+ | 1.2351 | 9.0 | 5787 | 1.3803 | 0.5515 | 0.5183 | 0.5515 | 0.2800 | 0.3399 | 0.0540 | 0.0549 | 0.9418 | 0.9662 | 0.5515 | 0.3399 | 0.5515 | 0.2922 | 0.5183 |
75
+ | 1.1161 | 10.0 | 6430 | 1.3406 | 0.5747 | 0.5342 | 0.5747 | 0.2900 | 0.3575 | 0.0502 | 0.0502 | 0.9453 | 0.9680 | 0.5747 | 0.3575 | 0.5747 | 0.3016 | 0.5351 |
76
+ | 0.9747 | 11.0 | 7073 | 1.3810 | 0.6150 | 0.5606 | 0.6150 | 0.3084 | 0.3747 | 0.0444 | 0.0428 | 0.9437 | 0.9706 | 0.6150 | 0.3747 | 0.6150 | 0.3262 | 0.5766 |
77
+ | 0.9145 | 12.0 | 7716 | 1.2736 | 0.6197 | 0.5857 | 0.6197 | 0.3199 | 0.3808 | 0.0421 | 0.0420 | 0.9508 | 0.9714 | 0.6197 | 0.3808 | 0.6197 | 0.3330 | 0.5913 |
78
+ | 0.8879 | 13.0 | 8359 | 1.3463 | 0.6352 | 0.5915 | 0.6352 | 0.3195 | 0.3877 | 0.0398 | 0.0394 | 0.9527 | 0.9725 | 0.6352 | 0.3877 | 0.6352 | 0.3368 | 0.6019 |
79
+ | 0.8034 | 14.0 | 9002 | 1.3203 | 0.6313 | 0.5913 | 0.6313 | 0.3223 | 0.3887 | 0.0402 | 0.0400 | 0.9523 | 0.9722 | 0.6313 | 0.3887 | 0.6313 | 0.3408 | 0.6029 |
80
+ | 0.7438 | 15.0 | 9645 | 1.3313 | 0.6344 | 0.5926 | 0.6344 | 0.3231 | 0.3898 | 0.0398 | 0.0395 | 0.9525 | 0.9725 | 0.6344 | 0.3898 | 0.6344 | 0.3416 | 0.6051 |
81
 
82
 
83
  ### Framework versions
runs/Apr13_22-36-59_8b05f59ca40c/events.out.tfevents.1713047820.8b05f59ca40c.34.14 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:018af2cb1c8d0ce1a4ab145f2b9200853c0d9167c5015fd2508fbe3df8718772
3
- size 25251
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d45354990d4465784550d2e9ef0e89ad0e38f8d911ac72fb3387f239fdc75b3f
3
+ size 25605