Hugging Face's logo

tinutmap
/
categor_ai

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Model card Files
xet
 Community
tinutmap commited on
Commit
7a90e5c
·
verified ·
1 Parent(s): f179568

End of training

Browse files
Files changed (1) hide show
  1. README.md +23 -13
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
17
 
18
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
- - Loss: 1.1572
21
- - Accuracy: 0.8667
22
 
23
  ## Model description
24
 
@@ -43,22 +43,32 @@ The following hyperparameters were used during training:
43
  - seed: 42
44
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
  - lr_scheduler_type: linear
46
- - num_epochs: 10
47
 
48
  ### Training results
49
 
50
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
52
- | No log | 1.0 | 13 | 2.4212 | 0.3667 |
53
- | No log | 2.0 | 26 | 2.1071 | 0.5889 |
54
- | No log | 3.0 | 39 | 1.8415 | 0.7444 |
55
- | No log | 4.0 | 52 | 1.6342 | 0.8 |
56
- | No log | 5.0 | 65 | 1.4824 | 0.8222 |
57
- | No log | 6.0 | 78 | 1.3583 | 0.8556 |
58
- | No log | 7.0 | 91 | 1.2725 | 0.8667 |
59
- | No log | 8.0 | 104 | 1.2061 | 0.8889 |
60
- | No log | 9.0 | 117 | 1.1675 | 0.8778 |
61
- | No log | 10.0 | 130 | 1.1572 | 0.8667 |
 
 
 
 
 
 
 
 
 
 
62
 
63
 
64
  ### Framework versions
 
17
 
18
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 0.5554
21
+ - Accuracy: 0.8889
22
 
23
  ## Model description
24
 
 
43
  - seed: 42
44
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
  - lr_scheduler_type: linear
46
+ - num_epochs: 20
47
 
48
  ### Training results
49
 
50
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
52
+ | No log | 1.0 | 13 | 2.4132 | 0.3667 |
53
+ | No log | 2.0 | 26 | 2.0787 | 0.5889 |
54
+ | No log | 3.0 | 39 | 1.7813 | 0.7778 |
55
+ | No log | 4.0 | 52 | 1.5379 | 0.8111 |
56
+ | No log | 5.0 | 65 | 1.3456 | 0.8667 |
57
+ | No log | 6.0 | 78 | 1.1728 | 0.8667 |
58
+ | No log | 7.0 | 91 | 1.0378 | 0.8889 |
59
+ | No log | 8.0 | 104 | 0.9195 | 0.8889 |
60
+ | No log | 9.0 | 117 | 0.8388 | 0.8889 |
61
+ | No log | 10.0 | 130 | 0.7984 | 0.8778 |
62
+ | No log | 11.0 | 143 | 0.7203 | 0.8889 |
63
+ | No log | 12.0 | 156 | 0.6822 | 0.8667 |
64
+ | No log | 13.0 | 169 | 0.6302 | 0.8889 |
65
+ | No log | 14.0 | 182 | 0.6128 | 0.8889 |
66
+ | No log | 15.0 | 195 | 0.5900 | 0.8889 |
67
+ | No log | 16.0 | 208 | 0.5819 | 0.8889 |
68
+ | No log | 17.0 | 221 | 0.5695 | 0.8889 |
69
+ | No log | 18.0 | 234 | 0.5624 | 0.8889 |
70
+ | No log | 19.0 | 247 | 0.5568 | 0.8889 |
71
+ | No log | 20.0 | 260 | 0.5554 | 0.8889 |
72
 
73
 
74
  ### Framework versions