File size: 3,616 Bytes
9b9ebe1
 
 
 
 
 
 
 
 
85b647c
caf9d9f
 
 
 
 
 
 
 
 
9b9ebe1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
caf9d9f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9b9ebe1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- banking77
metrics:
- accuracy
- f1
widget:
- text: Could you assist me in finding my lost card?
  example_title: Example 1
- text: I found my lost card. Am I still able to use it?
  example_title: Example 2
- text: "Hey, I thought my topup was all done but now the money is gone again \u2013\
    \ what\u2019s up with that?"
  example_title: Example 3
- text: "Tell me why my topup wouldn\u2019t go through?"
  example_title: Example 4
model-index:
- name: distilbert-base-uncased-finetuned-banking77
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: banking77
      type: banking77
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.925
    - name: F1
      type: f1
      value: 0.925018570680639
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: banking77
      type: banking77
      config: default
      split: test
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.925
      verified: true
    - name: Precision Macro
      type: precision
      value: 0.9282769473964405
      verified: true
    - name: Precision Micro
      type: precision
      value: 0.925
      verified: true
    - name: Precision Weighted
      type: precision
      value: 0.9282769473964405
      verified: true
    - name: Recall Macro
      type: recall
      value: 0.9250000000000002
      verified: true
    - name: Recall Micro
      type: recall
      value: 0.925
      verified: true
    - name: Recall Weighted
      type: recall
      value: 0.925
      verified: true
    - name: F1 Macro
      type: f1
      value: 0.9250185706806391
      verified: true
    - name: F1 Micro
      type: f1
      value: 0.925
      verified: true
    - name: F1 Weighted
      type: f1
      value: 0.925018570680639
      verified: true
    - name: loss
      type: loss
      value: 0.2934279143810272
      verified: true
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilbert-base-uncased-finetuned-banking77

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the banking77 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2935
- Accuracy: 0.925
- F1: 0.9250

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 9.686210354742596e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 126  | 1.1457          | 0.7896   | 0.7685 |
| No log        | 2.0   | 252  | 0.4673          | 0.8906   | 0.8889 |
| No log        | 3.0   | 378  | 0.3488          | 0.9150   | 0.9151 |
| 0.9787        | 4.0   | 504  | 0.3238          | 0.9180   | 0.9179 |
| 0.9787        | 5.0   | 630  | 0.3126          | 0.9225   | 0.9226 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.11.6