File size: 2,034 Bytes
a6346af
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: category-1-delivery-cancellation-distilbert-base-cased-v1
  results: []
---

<!-- 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. -->

# category-1-delivery-cancellation-distilbert-base-cased-v1

This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2696
- Accuracy: 0.9397

## 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: 2e-05
- train_batch_size: 60
- eval_batch_size: 60
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 334  | 0.2828          | 0.8999   |
| 0.2294        | 2.0   | 668  | 0.2118          | 0.9283   |
| 0.1448        | 3.0   | 1002 | 0.1580          | 0.9446   |
| 0.1448        | 4.0   | 1336 | 0.2625          | 0.9156   |
| 0.1013        | 5.0   | 1670 | 0.2521          | 0.9264   |
| 0.0731        | 6.0   | 2004 | 0.2462          | 0.9356   |
| 0.0731        | 7.0   | 2338 | 0.2330          | 0.9405   |
| 0.0497        | 8.0   | 2672 | 0.2507          | 0.9393   |
| 0.0389        | 9.0   | 3006 | 0.2696          | 0.9386   |
| 0.0389        | 10.0  | 3340 | 0.2696          | 0.9397   |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.3.0
- Datasets 2.20.0
- Tokenizers 0.19.1