File size: 2,736 Bytes
e08753f
 
 
 
 
39f701f
e08753f
 
 
 
 
 
39f701f
e08753f
 
 
39f701f
 
 
e08753f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
39f701f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e08753f
 
 
 
 
 
 
 
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
---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_mechanics_task8_fold0
  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. -->

# arabert_baseline_mechanics_task8_fold0

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4456
- Qwk: 0.7094
- Mse: 0.4456

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Qwk    | Mse    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| No log        | 0.5   | 2    | 1.7489          | 0.0491 | 1.7489 |
| No log        | 1.0   | 4    | 1.3896          | 0.1642 | 1.3896 |
| No log        | 1.5   | 6    | 1.1796          | 0.3277 | 1.1796 |
| No log        | 2.0   | 8    | 0.9747          | 0.4703 | 0.9747 |
| No log        | 2.5   | 10   | 0.8441          | 0.4560 | 0.8441 |
| No log        | 3.0   | 12   | 0.7876          | 0.4560 | 0.7876 |
| No log        | 3.5   | 14   | 0.7251          | 0.5758 | 0.7251 |
| No log        | 4.0   | 16   | 0.6598          | 0.5919 | 0.6598 |
| No log        | 4.5   | 18   | 0.6220          | 0.5919 | 0.6220 |
| No log        | 5.0   | 20   | 0.5659          | 0.6571 | 0.5659 |
| No log        | 5.5   | 22   | 0.5619          | 0.5709 | 0.5619 |
| No log        | 6.0   | 24   | 0.5885          | 0.5056 | 0.5885 |
| No log        | 6.5   | 26   | 0.5705          | 0.5056 | 0.5705 |
| No log        | 7.0   | 28   | 0.5149          | 0.7094 | 0.5149 |
| No log        | 7.5   | 30   | 0.4887          | 0.7094 | 0.4887 |
| No log        | 8.0   | 32   | 0.4700          | 0.7094 | 0.4700 |
| No log        | 8.5   | 34   | 0.4603          | 0.7094 | 0.4603 |
| No log        | 9.0   | 36   | 0.4527          | 0.7094 | 0.4527 |
| No log        | 9.5   | 38   | 0.4477          | 0.7821 | 0.4477 |
| No log        | 10.0  | 40   | 0.4456          | 0.7094 | 0.4456 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1