AIEKEK commited on
Commit
dde324e
1 Parent(s): 58cd17c

Training completed!

Browse files
Files changed (1) hide show
  1. README.md +9 -9
README.md CHANGED
@@ -23,10 +23,10 @@ model-index:
23
  metrics:
24
  - name: Accuracy
25
  type: accuracy
26
- value: 0.929
27
  - name: F1
28
  type: f1
29
- value: 0.9287765318513745
30
  ---
31
 
32
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
36
 
37
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
38
  It achieves the following results on the evaluation set:
39
- - Loss: 0.2110
40
- - Accuracy: 0.929
41
- - F1: 0.9288
42
 
43
  ## Model description
44
 
@@ -69,13 +69,13 @@ The following hyperparameters were used during training:
69
 
70
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
71
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
72
- | 0.8022 | 1.0 | 250 | 0.3077 | 0.909 | 0.9082 |
73
- | 0.2491 | 2.0 | 500 | 0.2110 | 0.929 | 0.9288 |
74
 
75
 
76
  ### Framework versions
77
 
78
- - Transformers 4.42.1
79
  - Pytorch 2.3.0
80
  - Datasets 2.16.1
81
- - Tokenizers 0.19.1
 
23
  metrics:
24
  - name: Accuracy
25
  type: accuracy
26
+ value: 0.9205
27
  - name: F1
28
  type: f1
29
+ value: 0.9200442708403018
30
  ---
31
 
32
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
36
 
37
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
38
  It achieves the following results on the evaluation set:
39
+ - Loss: 0.2206
40
+ - Accuracy: 0.9205
41
+ - F1: 0.9200
42
 
43
  ## Model description
44
 
 
69
 
70
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
71
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
72
+ | 0.8268 | 1.0 | 250 | 0.3130 | 0.905 | 0.9044 |
73
+ | 0.2529 | 2.0 | 500 | 0.2206 | 0.9205 | 0.9200 |
74
 
75
 
76
  ### Framework versions
77
 
78
+ - Transformers 4.37.2
79
  - Pytorch 2.3.0
80
  - Datasets 2.16.1
81
+ - Tokenizers 0.15.2