File size: 2,303 Bytes
a8c22c7
 
 
4c884ba
a8c22c7
 
 
 
 
 
 
 
 
 
 
 
4c884ba
 
 
 
a8c22c7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4c884ba
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a8c22c7
 
 
 
 
 
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
---
library_name: transformers
license: apache-2.0
base_model: team-lucid/hubert-base-korean
tags:
- generated_from_trainer
model-index:
- name: for_test
  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. -->

# for_test

This model is a fine-tuned version of [team-lucid/hubert-base-korean](https://huggingface.co/team-lucid/hubert-base-korean) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 10074.0381
- Cer: 0.8429

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 5400.8619     | 0.6369 | 300  | 13304.7881      | 1.0451 |
| 4024.1566     | 1.2739 | 600  | 11936.0117      | 0.9169 |
| 3685.2072     | 1.9108 | 900  | 11838.9512      | 0.8402 |
| 3836.7075     | 2.5478 | 1200 | 11351.3096      | 0.8275 |
| 3289.8719     | 3.1847 | 1500 | 11245.4717      | 0.8273 |
| 3506.6528     | 3.8217 | 1800 | 11008.6963      | 0.8322 |
| 3340.1028     | 4.4586 | 2100 | 10811.1230      | 0.8335 |
| 2946.4978     | 5.0955 | 2400 | 10763.3887      | 0.8341 |
| 3180.8653     | 5.7325 | 2700 | 10414.3926      | 0.8348 |
| 3159.9134     | 6.3694 | 3000 | 10376.6455      | 0.8354 |
| 2967.3987     | 7.0064 | 3300 | 10216.6924      | 0.8394 |
| 3072.4803     | 7.6433 | 3600 | 9977.7178       | 0.8387 |
| 3011.5284     | 8.2803 | 3900 | 10170.3740      | 0.8414 |
| 3042.4953     | 8.9172 | 4200 | 10057.4072      | 0.8420 |
| 3046.5066     | 9.5541 | 4500 | 10074.0381      | 0.8429 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1