File size: 2,122 Bytes
1acd2e2
833b100
 
 
 
 
 
 
1f62b22
 
 
 
 
 
 
d2dbb5d
 
 
6cfc1c0
 
833b100
 
6cfc1c0
833b100
6cfc1c0
833b100
 
 
6cfc1c0
833b100
 
 
6cfc1c0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
833b100
 
6cfc1c0
 
833b100
6cfc1c0
 
833b100
6cfc1c0
 
 
 
833b100
 
 
 
 
 
 
6cfc1c0
 
 
 
833b100
 
 
6cfc1c0
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
---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: hindi_gpt2
  results: []
widget:
- text: "अपने अनुप्रयोग को पहुंचनीयता व्यायाम"
- text: "जनतंत्र की सफलता केवल इस बात से नहीं हो सकती है कि हर"
- text: "अगर इसके बाद भी वे फैसले पर कायम रहते हैं और"
- text: "मामले का खुलासा होने के बाद"
- text: "My name is Julien and I like to"
- text: "My name is Thomas and my main"
inference:
  parameters:
    max_length: 200
---

<!-- 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. -->

# hindi_gpt2

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9187

## 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: 40
- eval_batch_size: 40
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 160
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 400
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.694         | 0.18  | 400  | 2.7361          |
| 2.3952        | 0.35  | 800  | 2.1608          |
| 2.1311        | 0.53  | 1200 | 2.0237          |
| 2.0282        | 0.71  | 1600 | 1.9518          |
| 1.9731        | 0.89  | 2000 | 1.9187          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3