File size: 1,857 Bytes
2142a94
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- reviews_with_drift
metrics:
- accuracy
- f1
model-index:
- name: distilbert_finetuned_reviews_with_drift
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: reviews_with_drift
      type: reviews_with_drift
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.854780153287616
    - name: F1
      type: f1
      value: 0.8547073010596418
---

<!-- 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_finetuned_reviews_with_drift

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the reviews_with_drift dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3822
- Accuracy: 0.8548
- F1: 0.8547

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4173        | 1.0   | 620  | 0.3519          | 0.8511   | 0.8511 |
| 0.259         | 2.0   | 1240 | 0.3822          | 0.8548   | 0.8547 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1