mental-bert-base-uncased_pirina_reddit
This model is a fine-tuned version of mental/mental-bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1471
- Accuracy: 0.9539
- Precision Micro: 0.9539
- Precision Macro: 0.9460
- Recall Micro: 0.9539
- Recall Macro: 0.9436
- F1 Micro: 0.9539
- F1 Macro: 0.9448
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Micro | Precision Macro | Recall Micro | Recall Macro | F1 Micro | F1 Macro |
---|---|---|---|---|---|---|---|---|---|---|
No log | 1.0 | 35 | 0.2240 | 0.9214 | 0.9214 | 0.9107 | 0.9214 | 0.8996 | 0.9214 | 0.9048 |
No log | 2.0 | 70 | 0.1414 | 0.9485 | 0.9485 | 0.9340 | 0.9485 | 0.9450 | 0.9485 | 0.9393 |
No log | 3.0 | 105 | 0.1320 | 0.9512 | 0.9512 | 0.9461 | 0.9512 | 0.9365 | 0.9512 | 0.9411 |
No log | 4.0 | 140 | 0.1420 | 0.9512 | 0.9512 | 0.9364 | 0.9512 | 0.9496 | 0.9512 | 0.9426 |
No log | 5.0 | 175 | 0.1427 | 0.9485 | 0.9485 | 0.9439 | 0.9485 | 0.9319 | 0.9485 | 0.9376 |
No log | 6.0 | 210 | 0.1462 | 0.9566 | 0.9566 | 0.9504 | 0.9566 | 0.9456 | 0.9566 | 0.9479 |
No log | 7.0 | 245 | 0.1471 | 0.9539 | 0.9539 | 0.9460 | 0.9539 | 0.9436 | 0.9539 | 0.9448 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0a0+872d972e41.nv24.08
- Datasets 2.21.0
- Tokenizers 0.19.1
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