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twitter-data-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: 0.5328
- Accuracy: 0.9274
- Precision: 0.9277
- Recall: 0.9274
- F1: 0.9275
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: 1e-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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3284 | 1.0 | 1783 | 0.2770 | 0.9140 | 0.9152 | 0.9140 | 0.9140 |
| 0.2422 | 2.0 | 3566 | 0.2388 | 0.9282 | 0.9297 | 0.9282 | 0.9283 |
| 0.207 | 3.0 | 5349 | 0.2291 | 0.9325 | 0.9337 | 0.9325 | 0.9326 |
| 0.1829 | 4.0 | 7132 | 0.2298 | 0.9341 | 0.9347 | 0.9341 | 0.9340 |
| 0.1665 | 5.0 | 8915 | 0.2493 | 0.9303 | 0.9309 | 0.9303 | 0.9304 |
| 0.142 | 6.0 | 10698 | 0.2749 | 0.9306 | 0.9309 | 0.9306 | 0.9305 |
| 0.1188 | 7.0 | 12481 | 0.2687 | 0.9279 | 0.9286 | 0.9279 | 0.9280 |
| 0.1013 | 8.0 | 14264 | 0.2900 | 0.9270 | 0.9273 | 0.9270 | 0.9271 |
| 0.0849 | 9.0 | 16047 | 0.3247 | 0.9261 | 0.9261 | 0.9261 | 0.9261 |
| 0.0723 | 10.0 | 17830 | 0.3549 | 0.9259 | 0.9266 | 0.9259 | 0.9261 |
| 0.057 | 11.0 | 19613 | 0.3706 | 0.9283 | 0.9288 | 0.9283 | 0.9284 |
| 0.0496 | 12.0 | 21396 | 0.4070 | 0.9258 | 0.9266 | 0.9258 | 0.9260 |
| 0.0423 | 13.0 | 23179 | 0.4361 | 0.9254 | 0.9262 | 0.9254 | 0.9256 |
| 0.0355 | 14.0 | 24962 | 0.4602 | 0.9297 | 0.9305 | 0.9297 | 0.9298 |
| 0.0291 | 15.0 | 26745 | 0.4859 | 0.9258 | 0.9259 | 0.9258 | 0.9258 |
| 0.0248 | 16.0 | 28528 | 0.5024 | 0.9273 | 0.9274 | 0.9273 | 0.9273 |
| 0.0219 | 17.0 | 30311 | 0.5093 | 0.9263 | 0.9264 | 0.9263 | 0.9263 |
| 0.0191 | 18.0 | 32094 | 0.5244 | 0.9280 | 0.9288 | 0.9280 | 0.9282 |
| 0.0171 | 19.0 | 33877 | 0.5290 | 0.9273 | 0.9276 | 0.9273 | 0.9274 |
| 0.0172 | 20.0 | 35660 | 0.5328 | 0.9274 | 0.9277 | 0.9274 | 0.9275 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1
