Model determines the financial topic of given tweets over 20 various topics. 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: 64
eval_batch_size: 64
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
No log
1.0
266
0.5152
0.8552
0.8504
0.8508
0.8552
0.7618
2.0
532
0.3999
0.8790
0.8781
0.8842
0.8790
0.7618
3.0
798
0.3628
0.8943
0.8940
0.8958
0.8943
0.16
4.0
1064
0.3776
0.8997
0.9001
0.9025
0.8997
0.16
5.0
1330
0.4286
0.8999
0.9002
0.9022
0.8999
0.058
6.0
1596
0.4500
0.9043
0.9042
0.9055
0.9043
0.058
7.0
1862
0.4689
0.9021
0.9017
0.9026
0.9021
0.0267
8.0
2128
0.4918
0.9031
0.9029
0.9039
0.9031
0.0267
9.0
2394
0.5030
0.9048
0.9049
0.9060
0.9048
0.0177
10.0
2660
0.5052
0.9033
0.9034
0.9044
0.9033
0.0177
11.0
2926
0.5265
0.9036
0.9034
0.9055
0.9036
0.013
12.0
3192
0.5267
0.9041
0.9041
0.9058
0.9041
0.013
13.0
3458
0.5090
0.9106
0.9106
0.9113
0.9106
0.0105
14.0
3724
0.5315
0.9067
0.9067
0.9080
0.9067
0.0105
15.0
3990
0.5339
0.9084
0.9084
0.9093
0.9084
0.0068
16.0
4256
0.5414
0.9072
0.9074
0.9088
0.9072
0.0051
17.0
4522
0.5460
0.9092
0.9091
0.9102
0.9092
0.0051
18.0
4788
0.5438
0.9072
0.9073
0.9081
0.9072
0.0035
19.0
5054
0.5474
0.9072
0.9073
0.9080
0.9072
0.0035
20.0
5320
0.5484
0.9079
0.9080
0.9087
0.9079
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2
Runs of nickmuchi finbert-tone-finetuned-finance-topic-classification on huggingface.co
87.2K
Total runs
-25
24-hour runs
885
3-day runs
562
7-day runs
-1.9K
30-day runs
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