Mateo GN commited on
Commit
db4407e
1 Parent(s): b52a192

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +4 -9
README.md CHANGED
@@ -14,23 +14,22 @@ should probably proofread and complete it, then remove this comment. -->
14
 
15
  # finetuning-pysentimiento-war-tweets
16
 
17
- This model is a fine-tuned version of [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis) on an unknown dataset.
18
- It achieves the following results on the evaluation set:
19
  - Loss: 1.7689
20
  - Accuracy: 0.7378
21
  - F1: 0.7456
22
 
23
  ## Model description
24
 
25
- More information needed
26
 
27
  ## Intended uses & limitations
28
 
29
- More information needed
30
 
31
  ## Training and evaluation data
32
 
33
- More information needed
34
 
35
  ## Training procedure
36
 
@@ -45,10 +44,6 @@ The following hyperparameters were used during training:
45
  - lr_scheduler_type: linear
46
  - num_epochs: 30
47
 
48
- ### Training results
49
-
50
-
51
-
52
  ### Framework versions
53
 
54
  - Transformers 4.20.1
14
 
15
  # finetuning-pysentimiento-war-tweets
16
 
17
+ This model is a fine-tuned version of [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis) on a dataset of 1500 tweets from Peruvian accounts. It achieves the following results on the evaluation set:
 
18
  - Loss: 1.7689
19
  - Accuracy: 0.7378
20
  - F1: 0.7456
21
 
22
  ## Model description
23
 
24
+ This model in a fine-tuned version of [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis) using five labels: **pro_russia**, **against_ukraine**, **neutral**, **against_russia**, **pro_ukraine**.
25
 
26
  ## Intended uses & limitations
27
 
28
+ This model shall be used to classify text (more specifically, Spanish tweets) as expressing a position concerning the Russo-Ukrainian war.
29
 
30
  ## Training and evaluation data
31
 
32
+ We used an 80/20 training/test split on the aforementioned dataset.
33
 
34
  ## Training procedure
35
 
44
  - lr_scheduler_type: linear
45
  - num_epochs: 30
46
 
 
 
 
 
47
  ### Framework versions
48
 
49
  - Transformers 4.20.1