slac-new-appearance-class_weight
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6580
- Accuracy: 0.9722
- F1 Macro: 0.9501
- Precision Macro: 0.9550
- Recall Macro: 0.9453
- F1 Micro: 0.9722
- Precision Micro: 0.9722
- Recall Micro: 0.9722
- Total Tf: [1504, 43, 1504, 43]
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 188
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | F1 Micro | Precision Micro | Recall Micro | Total Tf |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.3413 | 1.0 | 189 | 0.3518 | 0.9657 | 0.9383 | 0.9445 | 0.9323 | 0.9657 | 0.9657 | 0.9657 | [1494, 53, 1494, 53] |
| 0.1621 | 2.0 | 378 | 0.2254 | 0.9741 | 0.9547 | 0.9482 | 0.9616 | 0.9741 | 0.9741 | 0.9741 | [1507, 40, 1507, 40] |
| 0.1143 | 3.0 | 567 | 0.2430 | 0.9754 | 0.9571 | 0.9493 | 0.9655 | 0.9754 | 0.9754 | 0.9754 | [1509, 38, 1509, 38] |
| 0.0412 | 4.0 | 756 | 0.3585 | 0.9767 | 0.9586 | 0.9586 | 0.9586 | 0.9767 | 0.9767 | 0.9767 | [1511, 36, 1511, 36] |
| 0.04 | 5.0 | 945 | 0.3294 | 0.9735 | 0.9537 | 0.9465 | 0.9613 | 0.9735 | 0.9735 | 0.9735 | [1506, 41, 1506, 41] |
| 0.0262 | 6.0 | 1134 | 0.4335 | 0.9761 | 0.9578 | 0.9544 | 0.9613 | 0.9761 | 0.9761 | 0.9761 | [1510, 37, 1510, 37] |
| 0.0074 | 7.0 | 1323 | 0.4707 | 0.9761 | 0.9577 | 0.9556 | 0.9598 | 0.9761 | 0.9761 | 0.9761 | [1510, 37, 1510, 37] |
| 0.0123 | 8.0 | 1512 | 0.4739 | 0.9754 | 0.9566 | 0.9539 | 0.9594 | 0.9754 | 0.9754 | 0.9754 | [1509, 38, 1509, 38] |
| 0.0097 | 9.0 | 1701 | 0.5910 | 0.9729 | 0.9516 | 0.9530 | 0.9502 | 0.9729 | 0.9729 | 0.9729 | [1505, 42, 1505, 42] |
| 0.0005 | 10.0 | 1890 | 0.4584 | 0.9729 | 0.9525 | 0.9459 | 0.9593 | 0.9729 | 0.9729 | 0.9729 | [1505, 42, 1505, 42] |
| 0.0194 | 11.0 | 2079 | 0.6482 | 0.9729 | 0.9515 | 0.9543 | 0.9487 | 0.9729 | 0.9729 | 0.9729 | [1505, 42, 1505, 42] |
| 0.012 | 12.0 | 2268 | 0.7129 | 0.9716 | 0.9487 | 0.9558 | 0.9419 | 0.9716 | 0.9716 | 0.9716 | [1503, 44, 1503, 44] |
| 0.0036 | 13.0 | 2457 | 0.5640 | 0.9729 | 0.9518 | 0.9518 | 0.9518 | 0.9729 | 0.9729 | 0.9729 | [1505, 42, 1505, 42] |
| 0.0003 | 14.0 | 2646 | 0.6578 | 0.9722 | 0.9501 | 0.9550 | 0.9453 | 0.9722 | 0.9722 | 0.9722 | [1504, 43, 1504, 43] |
| 0.0012 | 15.0 | 2835 | 0.6580 | 0.9722 | 0.9501 | 0.9550 | 0.9453 | 0.9722 | 0.9722 | 0.9722 | [1504, 43, 1504, 43] |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
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