Karols commited on
Commit
0752174
1 Parent(s): 5088701

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +62 -0
README.md ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language: es
3
+ tags:
4
+ - text-classification
5
+ - financial-sentiment-analysis
6
+ - sentiment-analysis
7
+ datasets:
8
+ - datasets/financial_phrasebank
9
+ metrics:
10
+ - f1
11
+ - accuracy
12
+ - precision
13
+ - recall
14
+ widget:
15
+ - text: "Las ventas netas aumentaron un 30%, hasta 36 millones de euros."
16
+ example_title: "Example 1"
17
+ - text: "Comienza el Black Friday. Lista de promociones en tienda."
18
+ example_title: "Example 2"
19
+ - text: "Las acciones de CDPROJEKT registraron la mayor caída entre las empresas cotizadas en la WSE."
20
+ example_title: "Example 3"
21
+ ---
22
+
23
+
24
+ # Finance Sentiment ES (base)
25
+
26
+ Finance Sentiment ES (base) is a model based on [bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) for analyzing sentiment of Spanish financial news. It was trained on the translated version of [Financial PhraseBank](https://www.researchgate.net/publication/251231107_Good_Debt_or_Bad_Debt_Detecting_Semantic_Orientations_in_Economic_Texts) by Malo et al. (20014) for 10 epochs on single RTX3090 gpu.
27
+
28
+ The model will give you a three labels: positive, negative and neutral.
29
+
30
+ ## How to use
31
+
32
+ You can use this model directly with a pipeline for sentiment-analysis:
33
+
34
+ ```python
35
+ from transformers import pipeline
36
+
37
+ nlp = pipeline("sentiment-analysis", model="bardsai/finance-sentiment-es-base")
38
+ nlp("Las ventas netas aumentaron un 30%, hasta 36 millones de euros.")
39
+ ```
40
+ ```bash
41
+ [{'label': 'positive', 'score': 0.9987998807375955}]
42
+ ```
43
+
44
+ ## Performance
45
+ | Metric | Value |
46
+ | --- | ----------- |
47
+ | f1 macro | 0.973 |
48
+ | precision macro | 0.974 |
49
+ | recall macro | 0.972 |
50
+ | accuracy | 0.978 |
51
+ | samples per second | 135.1 |
52
+
53
+ (The performance was evaluated on RTX 3090 gpu)
54
+
55
+ ## Changelog
56
+ - 2023-09-18: Initial release
57
+
58
+ ## About bards.ai
59
+
60
+ At bards.ai, we focus on providing machine learning expertise and skills to our partners, particularly in the areas of nlp, machine vision and time series analysis. Our team is located in Wroclaw, Poland. Please visit our website for more information: [bards.ai](https://bards.ai/)
61
+
62
+ Let us know if you use our model :). Also, if you need any help, feel free to contact us at info@bards.ai