Hugging Face's logo

Vasanth
/
bert_emo_classifier

Text Classification Transformers PyTorch TensorBoard
bert generated_from_trainer Inference Endpoints
Model card Files Metrics Community
2
Vasanth commited on
Commit
ae2bcea
•
1 Parent(s): 39c86cc

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +17 -17
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
16
 
17
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
18
  It achieves the following results on the evaluation set:
19
- - Loss: 0.2715
20
 
21
  ## Model description
22
 
@@ -47,22 +47,22 @@ The following hyperparameters were used during training:
47
 
48
  | Training Loss | Epoch | Step | Validation Loss |
49
  |:-------------:|:-----:|:----:|:---------------:|
50
- | 0.888 | 0.25 | 500 | 0.4122 |
51
- | 0.338 | 0.5 | 1000 | 0.2967 |
52
- | 0.2527 | 0.75 | 1500 | 0.2798 |
53
- | 0.2389 | 1.0 | 2000 | 0.2554 |
54
- | 0.161 | 1.25 | 2500 | 0.2172 |
55
- | 0.1687 | 1.5 | 3000 | 0.1868 |
56
- | 0.136 | 1.75 | 3500 | 0.1909 |
57
- | 0.1733 | 2.0 | 4000 | 0.2073 |
58
- | 0.1088 | 2.25 | 4500 | 0.2176 |
59
- | 0.1109 | 2.5 | 5000 | 0.2136 |
60
- | 0.1241 | 2.75 | 5500 | 0.2356 |
61
- | 0.1232 | 3.0 | 6000 | 0.2241 |
62
- | 0.074 | 3.25 | 6500 | 0.2542 |
63
- | 0.0761 | 3.5 | 7000 | 0.2682 |
64
- | 0.0751 | 3.75 | 7500 | 0.2674 |
65
- | 0.0652 | 4.0 | 8000 | 0.2715 |
66
 
67
 
68
  ### Framework versions
16
 
17
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
18
  It achieves the following results on the evaluation set:
19
+ - Loss: 0.2748
20
 
21
  ## Model description
22
 
47
 
48
  | Training Loss | Epoch | Step | Validation Loss |
49
  |:-------------:|:-----:|:----:|:---------------:|
50
+ | 0.9063 | 0.25 | 500 | 0.4845 |
51
+ | 0.3362 | 0.5 | 1000 | 0.3492 |
52
+ | 0.2759 | 0.75 | 1500 | 0.2819 |
53
+ | 0.2521 | 1.0 | 2000 | 0.2464 |
54
+ | 0.1705 | 1.25 | 2500 | 0.2345 |
55
+ | 0.1841 | 1.5 | 3000 | 0.2013 |
56
+ | 0.1428 | 1.75 | 3500 | 0.1926 |
57
+ | 0.1747 | 2.0 | 4000 | 0.1866 |
58
+ | 0.1082 | 2.25 | 4500 | 0.2302 |
59
+ | 0.1142 | 2.5 | 5000 | 0.2118 |
60
+ | 0.1205 | 2.75 | 5500 | 0.2318 |
61
+ | 0.1135 | 3.0 | 6000 | 0.2306 |
62
+ | 0.0803 | 3.25 | 6500 | 0.2625 |
63
+ | 0.0745 | 3.5 | 7000 | 0.2850 |
64
+ | 0.085 | 3.75 | 7500 | 0.2719 |
65
+ | 0.0701 | 4.0 | 8000 | 0.2748 |
66
 
67
 
68
  ### Framework versions