File size: 2,172 Bytes
2c77105
f8c249f
 
 
 
 
 
 
 
 
 
2c77105
 
f8c249f
 
2c77105
f8c249f
2c77105
f8c249f
 
 
 
2c77105
f8c249f
2c77105
f8c249f
2c77105
f8c249f
2c77105
f8c249f
2c77105
f8c249f
2c77105
f8c249f
2c77105
f8c249f
2c77105
f8c249f
2c77105
f8c249f
 
 
 
 
 
 
 
2c77105
f8c249f
2c77105
f8c249f
 
 
 
 
 
 
 
 
 
 
 
2c77105
 
f8c249f
2c77105
f8c249f
 
 
 
 
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1143
- Accuracy: {'accuracy': 0.885}

## 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  | 0.3907          | {'accuracy': 0.87}  |
| 0.4307        | 2.0   | 500  | 0.4413          | {'accuracy': 0.886} |
| 0.4307        | 3.0   | 750  | 0.7302          | {'accuracy': 0.879} |
| 0.1513        | 4.0   | 1000 | 0.7659          | {'accuracy': 0.882} |
| 0.1513        | 5.0   | 1250 | 0.7540          | {'accuracy': 0.877} |
| 0.0662        | 6.0   | 1500 | 0.8800          | {'accuracy': 0.886} |
| 0.0662        | 7.0   | 1750 | 1.0128          | {'accuracy': 0.885} |
| 0.0086        | 8.0   | 2000 | 1.0446          | {'accuracy': 0.884} |
| 0.0086        | 9.0   | 2250 | 1.1049          | {'accuracy': 0.884} |
| 0.0026        | 10.0  | 2500 | 1.1143          | {'accuracy': 0.885} |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2