cope-ap-g2b-2c-hs.s1.5.9-sx.s1.5.9o-vl.s1.5.9-hr.s5-sh.s5.l5e5-e5-d25-r8
This model is a fine-tuned version of google/gemma-2b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4995
- F1: 0.8471
- Precision: 0.8045
- Recall: 0.8944
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
---|---|---|---|---|---|---|
0.1173 | 1.0 | 1148 | 0.2132 | 0.8343 | 0.7966 | 0.8758 |
0.143 | 2.0 | 2296 | 0.2483 | 0.8442 | 0.7760 | 0.9255 |
0.1892 | 3.0 | 3444 | 0.2780 | 0.8523 | 0.7853 | 0.9317 |
0.0564 | 4.0 | 4593 | 0.4343 | 0.8638 | 0.8098 | 0.9255 |
0.0003 | 5.0 | 5740 | 0.4995 | 0.8471 | 0.8045 | 0.8944 |
Framework versions
- PEFT 0.8.2
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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