CeLLaTe3.0_Base_no_vague_adapted_pubmed_gaz_lr_5e-5
This model is a fine-tuned version of Mardiyyah/cellate2.0-tapt_base-LR_5e-05 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1410
- Precision: 0.8308
- Recall: 0.8511
- F1: 0.8408
- Accuracy: 0.9670
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: 16
- seed: 3407
- 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_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.0287 | 1.0417 | 100 | 0.3060 | 0.3496 | 0.2434 | 0.2870 | 0.9111 |
| 0.1964 | 2.0833 | 200 | 0.1409 | 0.7580 | 0.8360 | 0.7951 | 0.9628 |
| 0.0929 | 3.125 | 300 | 0.1408 | 0.8308 | 0.8511 | 0.8408 | 0.9670 |
| 0.0552 | 4.1667 | 400 | 0.1731 | 0.8381 | 0.8051 | 0.8212 | 0.9656 |
| 0.0365 | 5.2083 | 500 | 0.2119 | 0.8395 | 0.7491 | 0.7917 | 0.9609 |
| 0.0259 | 6.25 | 600 | 0.1992 | 0.8023 | 0.7605 | 0.7808 | 0.9608 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0
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Mardiyyah/cellate2.0-tapt_base-LR_5e-05