File size: 2,557 Bytes
82f7040
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
20f01aa
 
82f7040
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
22c49fe
82f7040
 
 
 
 
cabe5bb
82f7040
 
 
 
 
20f01aa
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82f7040
 
 
 
c9d7764
82f7040
c9d7764
82f7040
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
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: interview_classifier
  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. -->

# interview_classifier

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: 0.5073
- Accuracy: 0.9444

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 54   | 2.2473          | 0.1019   |
| No log        | 2.0   | 108  | 2.1669          | 0.5370   |
| No log        | 3.0   | 162  | 2.0159          | 0.5370   |
| No log        | 4.0   | 216  | 1.8393          | 0.5556   |
| No log        | 5.0   | 270  | 1.6508          | 0.6667   |
| No log        | 6.0   | 324  | 1.4806          | 0.7037   |
| No log        | 7.0   | 378  | 1.3298          | 0.7593   |
| No log        | 8.0   | 432  | 1.1826          | 0.8241   |
| No log        | 9.0   | 486  | 1.0571          | 0.8611   |
| 1.7901        | 10.0  | 540  | 0.9303          | 0.8611   |
| 1.7901        | 11.0  | 594  | 0.8432          | 0.8889   |
| 1.7901        | 12.0  | 648  | 0.7697          | 0.9259   |
| 1.7901        | 13.0  | 702  | 0.6979          | 0.9352   |
| 1.7901        | 14.0  | 756  | 0.6440          | 0.9352   |
| 1.7901        | 15.0  | 810  | 0.6008          | 0.9352   |
| 1.7901        | 16.0  | 864  | 0.5666          | 0.9444   |
| 1.7901        | 17.0  | 918  | 0.5383          | 0.9444   |
| 1.7901        | 18.0  | 972  | 0.5220          | 0.9444   |
| 0.7773        | 19.0  | 1026 | 0.5114          | 0.9444   |
| 0.7773        | 20.0  | 1080 | 0.5073          | 0.9444   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1