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ProsusAI-finbert-sentiment-finetuned-memes
This model is a fine-tuned version of ProsusAI/finbert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3093
- Accuracy: 0.8407
- Precision: 0.8412
- Recall: 0.8407
- F1: 0.8409
Model description
More information needed
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.467 | 1.0 | 2147 | 0.4178 | 0.7898 | 0.7882 | 0.7898 | 0.7883 |
0.3669 | 2.0 | 4294 | 0.4876 | 0.7940 | 0.8073 | 0.7940 | 0.7961 |
0.2801 | 3.0 | 6441 | 0.6222 | 0.8040 | 0.8034 | 0.8040 | 0.8037 |
0.2402 | 4.0 | 8588 | 0.8062 | 0.8229 | 0.8219 | 0.8229 | 0.8211 |
0.2099 | 5.0 | 10735 | 0.9219 | 0.8197 | 0.8263 | 0.8197 | 0.8211 |
0.16 | 6.0 | 12882 | 1.0393 | 0.8312 | 0.8342 | 0.8312 | 0.8321 |
0.1192 | 7.0 | 15029 | 1.1263 | 0.8333 | 0.8337 | 0.8333 | 0.8335 |
0.0979 | 8.0 | 17176 | 1.2048 | 0.8328 | 0.8324 | 0.8328 | 0.8326 |
0.0691 | 9.0 | 19323 | 1.2891 | 0.8323 | 0.8327 | 0.8323 | 0.8325 |
0.0458 | 10.0 | 21470 | 1.3093 | 0.8407 | 0.8412 | 0.8407 | 0.8409 |
Framework versions
- Transformers 4.13.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 1.15.2.dev0
- Tokenizers 0.10.1