File size: 2,078 Bytes
d2fc594
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6743a80
d2fc594
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6743a80
d2fc594
 
 
 
6743a80
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d2fc594
 
 
 
 
 
 
 
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
---
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: bert-concat-3
  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. -->

# bert-concat-3

This model is a fine-tuned version of [](https://huggingface.co/) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 5.8028

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 35
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.5215        | 2.11  | 1000  | 6.1057          |
| 5.9958        | 4.22  | 2000  | 6.0199          |
| 5.9066        | 6.33  | 3000  | 5.9833          |
| 5.8449        | 8.44  | 4000  | 5.9594          |
| 5.7913        | 10.55 | 5000  | 5.9176          |
| 5.7418        | 12.66 | 6000  | 5.8949          |
| 5.6901        | 14.77 | 7000  | 5.8753          |
| 5.6485        | 16.88 | 8000  | 5.8592          |
| 5.6238        | 18.99 | 9000  | 5.8509          |
| 5.6704        | 21.1  | 10000 | 5.8856          |
| 5.6375        | 23.21 | 11000 | 5.8703          |
| 5.6039        | 25.32 | 12000 | 5.8635          |
| 5.5756        | 27.43 | 13000 | 5.8533          |
| 5.5437        | 29.54 | 14000 | 5.8408          |
| 5.5189        | 31.65 | 15000 | 5.8154          |
| 5.4982        | 33.76 | 16000 | 5.8028          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3