File size: 2,596 Bytes
124430e
cca4c10
eae9ad4
 
124430e
 
 
 
 
2e43dfd
 
b1fc962
 
124430e
 
 
eae9ad4
124430e
baba3b3
124430e
 
 
9f4d566
124430e
d92e70e
124430e
9f4d566
124430e
d92e70e
124430e
b1fc962
d92e70e
 
 
 
 
 
 
6441086
 
d92e70e
baba3b3
d92e70e
9f4d566
d92e70e
 
 
baba3b3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d92e70e
 
 
 
baba3b3
 
 
 
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
79
80
81
82
83
---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: TenaliAI-FinTech-v1
  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. -->

# TenaliAI-FinTech-v1

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7505

## 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: 25

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 1.6215        | 1.0   | 5485   | 1.3611          |
| 0.9667        | 2.0   | 10970  | 0.9202          |
| 0.7911        | 3.0   | 16455  | 0.8125          |
| 0.7406        | 4.0   | 21940  | 0.7648          |
| 0.6934        | 5.0   | 27425  | 0.7711          |
| 0.6457        | 6.0   | 32910  | 0.7546          |
| 0.6511        | 7.0   | 38395  | 0.7506          |
| 0.6244        | 8.0   | 43880  | 0.7548          |
| 0.6076        | 9.0   | 49365  | 0.7505          |
| 0.6003        | 10.0  | 54850  | 0.7579          |
| 0.5649        | 11.0  | 60335  | 0.7583          |
| 0.5616        | 12.0  | 65820  | 0.7597          |
| 0.5688        | 13.0  | 71305  | 0.7685          |
| 0.5571        | 14.0  | 76790  | 0.7705          |
| 0.5709        | 15.0  | 82275  | 0.7666          |
| 0.56          | 16.0  | 87760  | 0.7790          |
| 0.5474        | 17.0  | 93245  | 0.7798          |
| 0.5431        | 18.0  | 98730  | 0.7906          |
| 0.541         | 19.0  | 104215 | 0.7987          |
| 0.5426        | 20.0  | 109700 | 0.7953          |
| 0.5534        | 21.0  | 115185 | 0.7978          |
| 0.5541        | 22.0  | 120670 | 0.7929          |
| 0.538         | 23.0  | 126155 | 0.7997          |
| 0.5463        | 24.0  | 131640 | 0.8205          |
| 0.5606        | 25.0  | 137125 | 0.8226          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1