File size: 1,986 Bytes
15e6b15
 
 
 
 
 
 
 
62f842e
15e6b15
 
 
 
 
 
62f842e
15e6b15
 
 
62f842e
 
15e6b15
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
62f842e
 
 
 
 
 
 
 
 
 
 
15e6b15
 
 
 
 
 
 
 
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
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: newsdata-bert
  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. -->

# newsdata-bert

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0878
- Accuracy: 0.8087

## 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: 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: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.3096        | 0.0859 | 5000  | 1.4907          | 0.7014   |
| 1.2402        | 0.1718 | 10000 | 1.2411          | 0.7285   |
| 1.1273        | 0.2577 | 15000 | 1.3464          | 0.7514   |
| 1.0028        | 0.3436 | 20000 | 1.4583          | 0.7323   |
| 0.9333        | 0.4295 | 25000 | 1.2102          | 0.7713   |
| 0.9045        | 0.5155 | 30000 | 1.1515          | 0.7801   |
| 0.7642        | 0.6014 | 35000 | 1.1968          | 0.7873   |
| 0.8657        | 0.6873 | 40000 | 1.0961          | 0.7967   |
| 0.8082        | 0.7732 | 45000 | 1.1199          | 0.7977   |
| 0.7657        | 0.8591 | 50000 | 1.1115          | 0.8029   |
| 0.7556        | 0.9450 | 55000 | 1.0878          | 0.8087   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1