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finetuned-endpoints_classif_test_2-4_14_1259
This model is a fine-tuned version of ProsusAI/finbert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1479
- F1: 0.9533
- Accuracy: 0.9545
- Precision: 0.9593
- Recall: 0.9545
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: 5e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.8576 | 1.0 | 19 | 1.7069 | 0.2234 | 0.3864 | 0.1585 | 0.3864 |
| 1.4072 | 2.0 | 38 | 1.3519 | 0.4570 | 0.5227 | 0.4489 | 0.5227 |
| 1.0111 | 3.0 | 57 | 0.9178 | 0.7552 | 0.7955 | 0.7300 | 0.7955 |
| 0.6001 | 4.0 | 76 | 0.5478 | 0.7958 | 0.8409 | 0.7684 | 0.8409 |
| 0.3433 | 5.0 | 95 | 0.4193 | 0.8220 | 0.8409 | 0.8864 | 0.8409 |
| 0.1889 | 6.0 | 114 | 0.3115 | 0.8435 | 0.8636 | 0.9048 | 0.8636 |
| 0.1132 | 7.0 | 133 | 0.2479 | 0.9533 | 0.9545 | 0.9593 | 0.9545 |
| 0.071 | 8.0 | 152 | 0.1863 | 0.9531 | 0.9545 | 0.9601 | 0.9545 |
| 0.0437 | 9.0 | 171 | 0.1709 | 0.9533 | 0.9545 | 0.9593 | 0.9545 |
| 0.0324 | 10.0 | 190 | 0.1559 | 0.9533 | 0.9545 | 0.9593 | 0.9545 |
| 0.0233 | 11.0 | 209 | 0.1514 | 0.9533 | 0.9545 | 0.9593 | 0.9545 |
| 0.021 | 12.0 | 228 | 0.1479 | 0.9533 | 0.9545 | 0.9593 | 0.9545 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
