biorecall-flan-T5-base-lora
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0037
- Bertscore F1: 0.6125
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Bertscore F1 |
|---|---|---|---|---|
| No log | 1.0 | 438 | 2.0117 | 0.6085 |
| 2.2264 | 2.0 | 876 | 2.0107 | 0.6119 |
| 2.1942 | 3.0 | 1314 | 2.0036 | 0.6109 |
| 2.1696 | 4.0 | 1752 | 2.0032 | 0.6127 |
| 2.1786 | 5.0 | 2190 | 2.0037 | 0.6125 |
Framework versions
- PEFT 0.18.0
- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1