File size: 2,211 Bytes
49910c1 53d1a3f 49910c1 8bf08dd 49910c1 cff8dd4 49910c1 53d1a3f 49910c1 8bf08dd 49910c1 f4ea2c4 49910c1 f6790c1 49910c1 f6790c1 49910c1 f6790c1 49910c1 8bf08dd 53d1a3f 8bf08dd 9e5fc6e 49910c1 9e5fc6e 49910c1 |
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 81 82 83 84 85 86 87 88 89 90 |
---
license: apache-2.0
tags:
-
datasets:
- EXIST Dataset
- MeTwo Machismo and Sexism Twitter Identification dataset
metrics:
- accuracy
model-index:
- name: twitter_sexismo-finetuned-exist2021
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: EXIST Dataset
type: EXIST Dataset
args: es
metrics:
- name: Accuracy
type: accuracy
value: 0.83
---
# twitter_sexismo-finetuned-exist2021
This model is a fine-tuned version of [pysentimiento/robertuito-hate-speech](https://huggingface.co/pysentimiento/robertuito-hate-speech) on the EXIST dataset and + MeTwo: Machismo and Sexism Twitter Identification dataset https://github.com/franciscorodriguez92/MeTwo.
It achieves the following results on the evaluation set:
- Loss: 0.54
- Accuracy: 0.83
## Model description
Modelo para el Hackaton de Somos NLP para detección de sexismo en twitts en español
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- my_learning_rate = 5E-5
- my_adam_epsilon = 1E-8
- my_number_of_epochs = 8
- my_warmup = 3
- my_mini_batch_size = 32
- optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
Epoch Training Loss Validation Loss Accuracy F1 Precision Recall
1 0.389900 0.397857 0.827133 0.699620 0.786325 0.630137
2 0.064400 0.544625 0.831510 0.707224 0.794872 0.636986
3 0.004800 0.837723 0.818381 0.704626 0.733333 0.678082
4 0.000500 1.045066 0.820569 0.702899 0.746154 0.664384
5 0.000200 1.172727 0.805252 0.669145 0.731707 0.616438
6 0.000200 1.202422 0.827133 0.720848 0.744526 0.698630
7 0.000000 1.195012 0.827133 0.718861 0.748148 0.691781
8 0.000100 1.215515 0.824945 0.705882 0.761905 0.657534
9 0.000100 1.233099 0.827133 0.710623 0.763780 0.664384
10 0.000100 1.237268 0.829322 0.713235 0.769841 0.664384
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Tokenizers 0.11.6
|