File size: 2,167 Bytes
27b42ec
656ff4d
27b42ec
656ff4d
 
 
 
27b42ec
656ff4d
 
 
27b42ec
 
656ff4d
 
27b42ec
656ff4d
27b42ec
656ff4d
 
 
 
27b42ec
656ff4d
27b42ec
656ff4d
27b42ec
656ff4d
27b42ec
656ff4d
27b42ec
656ff4d
27b42ec
656ff4d
27b42ec
656ff4d
27b42ec
656ff4d
27b42ec
656ff4d
 
 
 
 
 
 
 
27b42ec
656ff4d
27b42ec
656ff4d
 
 
 
 
 
 
 
 
 
 
 
27b42ec
 
 
 
656ff4d
 
 
 
 
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
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-lora-text-classification
  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. -->

# distilbert-base-uncased-lora-text-classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3644
- Accuracy: {'accuracy': 0.858}

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- 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   | 250  | 0.3793          | {'accuracy': 0.856} |
| 0.435         | 2.0   | 500  | 0.5190          | {'accuracy': 0.858} |
| 0.435         | 3.0   | 750  | 0.8326          | {'accuracy': 0.857} |
| 0.2005        | 4.0   | 1000 | 0.9137          | {'accuracy': 0.856} |
| 0.2005        | 5.0   | 1250 | 1.0362          | {'accuracy': 0.862} |
| 0.0827        | 6.0   | 1500 | 1.2331          | {'accuracy': 0.852} |
| 0.0827        | 7.0   | 1750 | 1.2110          | {'accuracy': 0.856} |
| 0.033         | 8.0   | 2000 | 1.2963          | {'accuracy': 0.864} |
| 0.033         | 9.0   | 2250 | 1.3438          | {'accuracy': 0.863} |
| 0.0128        | 10.0  | 2500 | 1.3644          | {'accuracy': 0.858} |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.0
- Pytorch 2.1.1+cpu
- Datasets 2.15.0
- Tokenizers 0.15.0