File size: 4,502 Bytes
e845cd9 d15bb20 e845cd9 d15bb20 496ef70 e845cd9 5594698 496ef70 5594698 496ef70 5594698 496ef70 5594698 e845cd9 d15bb20 e845cd9 5594698 e845cd9 428a4a1 e845cd9 |
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 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 |
---
tags:
- generated_from_trainer
- financial-tweets-sentiment-analysis
- sentiment-analysis
- generated_from_trainer
- financial
- stocks
- sentiment
datasets:
- zeroshot/twitter-financial-news-sentiment
metrics:
- accuracy
- f1
- precision
- recall
widget:
- text: $LOW - Lowe's racks up another positive rating despite recession risk
example_title: Bullish Sentiment
- text: $HNHAF $HNHPD $AAPL - Trendforce cuts iPhone estimate after Foxconn delay
example_title: Bearish Sentiment
- text: 'Coin Toss: Morgan Stanley Raises Tesla Bull Case To $500, Keeps Bear Case
At $10'
example_title: Neutral Sentiment
base_model: yiyanghkust/finbert-tone
model-index:
- name: finbert-tone-finetuned-fintwitter-classification
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: twitter-financial-news-sentiment
type: finance
metrics:
- type: F1
value: 0.8838
name: F1
- type: accuracy
value: 0.884
name: accuracy
---
<!-- 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. -->
# finbert-tone-finetuned-fintwitter-classification
This model is a fine-tuned version of [yiyanghkust/finbert-tone](https://huggingface.co/yiyanghkust/finbert-tone) on [Twitter Financial News](https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4078
- Accuracy: 0.8840
- F1: 0.8838
- Precision: 0.8838
- Recall: 0.8840
## Model description
Model determines the financial sentiment of given tweets. Given the unbalanced distribution of the class labels, the weights were adjusted to pay attention to the less sampled labels which should increase overall performance..
## 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: 2e-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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6385 | 1.0 | 597 | 0.3688 | 0.8668 | 0.8693 | 0.8744 | 0.8668 |
| 0.3044 | 2.0 | 1194 | 0.3994 | 0.8744 | 0.8726 | 0.8739 | 0.8744 |
| 0.1833 | 3.0 | 1791 | 0.6212 | 0.8781 | 0.8764 | 0.8762 | 0.8781 |
| 0.1189 | 4.0 | 2388 | 0.8370 | 0.8740 | 0.8743 | 0.8748 | 0.8740 |
| 0.0759 | 5.0 | 2985 | 0.9107 | 0.8807 | 0.8798 | 0.8796 | 0.8807 |
| 0.0291 | 6.0 | 3582 | 0.9711 | 0.8836 | 0.8825 | 0.8821 | 0.8836 |
| 0.0314 | 7.0 | 4179 | 1.1305 | 0.8819 | 0.8811 | 0.8812 | 0.8819 |
| 0.0217 | 8.0 | 4776 | 1.0190 | 0.8811 | 0.8813 | 0.8816 | 0.8811 |
| 0.0227 | 9.0 | 5373 | 1.1940 | 0.8844 | 0.8832 | 0.8838 | 0.8844 |
| 0.0156 | 10.0 | 5970 | 1.2595 | 0.8752 | 0.8768 | 0.8801 | 0.8752 |
| 0.0135 | 11.0 | 6567 | 1.1931 | 0.8760 | 0.8768 | 0.8780 | 0.8760 |
| 0.009 | 12.0 | 7164 | 1.2154 | 0.8857 | 0.8852 | 0.8848 | 0.8857 |
| 0.0058 | 13.0 | 7761 | 1.3874 | 0.8748 | 0.8759 | 0.8776 | 0.8748 |
| 0.009 | 14.0 | 8358 | 1.4193 | 0.8740 | 0.8754 | 0.8780 | 0.8740 |
| 0.0042 | 15.0 | 8955 | 1.2999 | 0.8807 | 0.8800 | 0.8796 | 0.8807 |
| 0.0028 | 16.0 | 9552 | 1.3428 | 0.8802 | 0.8805 | 0.8817 | 0.8802 |
| 0.0029 | 17.0 | 10149 | 1.3959 | 0.8807 | 0.8807 | 0.8810 | 0.8807 |
| 0.0022 | 18.0 | 10746 | 1.4149 | 0.8827 | 0.8823 | 0.8824 | 0.8827 |
| 0.0037 | 19.0 | 11343 | 1.4078 | 0.8840 | 0.8838 | 0.8838 | 0.8840 |
| 0.001 | 20.0 | 11940 | 1.4236 | 0.8823 | 0.8823 | 0.8825 | 0.8823 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
|