File size: 1,987 Bytes
daa4854
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---

license: cc-by-sa-4.0
base_model: EMBEDDIA/sloberta
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_copa_sloberta
  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. -->

# fine_tuned_copa_sloberta



This model is a fine-tuned version of [EMBEDDIA/sloberta](https://huggingface.co/EMBEDDIA/sloberta) on an unknown dataset.

It achieves the following results on the evaluation set:

- Loss: 0.6931

- Accuracy: 0.51

- F1: 0.4611



## 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: 0.003
- 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
- training_steps: 400



### Training results



| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |

|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|

| 0.6967        | 1.0   | 50   | 0.6931          | 0.55     | 0.3903 |

| 0.7084        | 2.0   | 100  | 0.6931          | 0.55     | 0.3903 |

| 0.7031        | 3.0   | 150  | 0.6931          | 0.55     | 0.3903 |

| 0.7045        | 4.0   | 200  | 0.6931          | 0.49     | 0.4220 |

| 0.7119        | 5.0   | 250  | 0.6931          | 0.56     | 0.4124 |

| 0.6942        | 6.0   | 300  | 0.6931          | 0.55     | 0.3903 |

| 0.7146        | 7.0   | 350  | 0.6931          | 0.56     | 0.4124 |

| 0.7177        | 8.0   | 400  | 0.6931          | 0.51     | 0.4611 |





### Framework versions



- Transformers 4.40.1

- Pytorch 2.1.1+cu121

- Datasets 2.19.0

- Tokenizers 0.19.1