File size: 2,013 Bytes
6bbd188
ac28478
 
 
ae10871
ac28478
 
ae10871
 
ac28478
 
 
 
 
ae10871
ac28478
 
 
 
 
 
 
ae10871
ac28478
ae10871
6bbd188
 
ac28478
 
6bbd188
ac28478
6bbd188
ac28478
 
 
 
6bbd188
ac28478
6bbd188
ac28478
6bbd188
ac28478
6bbd188
ac28478
6bbd188
ac28478
6bbd188
ac28478
6bbd188
ac28478
6bbd188
ac28478
6bbd188
ac28478
 
 
 
 
 
 
 
6bbd188
ac28478
6bbd188
ac28478
 
 
 
 
 
 
6bbd188
 
ac28478
6bbd188
ac28478
 
 
 
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
---
base_model: distilbert/distilroberta-base
datasets:
- financial_phrasebank
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: my_miniroberta_model
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: financial_phrasebank
      type: financial_phrasebank
      config: sentences_allagree
      split: train
      args: sentences_allagree
    metrics:
    - type: accuracy
      value: 0.9713024282560706
      name: Accuracy
---

<!-- 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. -->

# my_miniroberta_model

This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1663
- Accuracy: 0.9713

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 227  | 0.2026          | 0.9338   |
| No log        | 2.0   | 454  | 0.1337          | 0.9669   |
| 0.2375        | 3.0   | 681  | 0.1639          | 0.9713   |
| 0.2375        | 4.0   | 908  | 0.1499          | 0.9735   |
| 0.0176        | 5.0   | 1135 | 0.1663          | 0.9713   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1