File size: 1,807 Bytes
3f5c735
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: mit
base_model: Ariffiq99/CRAB_xlm_roberta_base_finetuned
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: e_care_CRAB_xlm_roberta_base_finetuned
  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. -->

# e_care_CRAB_xlm_roberta_base_finetuned

This model is a fine-tuned version of [Ariffiq99/CRAB_xlm_roberta_base_finetuned](https://huggingface.co/Ariffiq99/CRAB_xlm_roberta_base_finetuned) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6454
- F1: 0.6998

## 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: 1e-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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6761        | 1.0   | 933  | 0.5951          | 0.6503 |
| 0.5912        | 2.0   | 1866 | 0.5577          | 0.6857 |
| 0.545         | 3.0   | 2799 | 0.5491          | 0.7012 |
| 0.4863        | 4.0   | 3732 | 0.5610          | 0.7055 |
| 0.437         | 5.0   | 4665 | 0.5820          | 0.6970 |
| 0.3981        | 6.0   | 5598 | 0.6024          | 0.6993 |
| 0.363         | 7.0   | 6531 | 0.6454          | 0.6998 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1