File size: 2,501 Bytes
a47e2a4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
---
library_name: peft
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
model-index:
- name: medical-qa-t5-lora
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# medical-qa-t5-lora
This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: 500
- num_epochs: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3794 | 16.8 | 50 | 1.9909 |
| 1.2119 | 33.4 | 100 | 0.4473 |
| 0.2431 | 50.0 | 150 | 0.0048 |
| 0.0343 | 66.8 | 200 | 0.0008 |
| 0.0118 | 83.4 | 250 | 0.0003 |
| 0.0068 | 100.0 | 300 | 0.0002 |
| 0.0042 | 116.8 | 350 | 0.0001 |
| 0.0028 | 133.4 | 400 | 0.0001 |
| 0.002 | 150.0 | 450 | 0.0000 |
| 0.0015 | 166.8 | 500 | 0.0000 |
| 0.0012 | 183.4 | 550 | 0.0000 |
| 0.0017 | 200.0 | 600 | 0.0000 |
| 0.0012 | 216.8 | 650 | 0.0000 |
| 0.0008 | 233.4 | 700 | 0.0000 |
| 0.0006 | 250.0 | 750 | 0.0000 |
| 0.0006 | 266.8 | 800 | 0.0000 |
| 0.0004 | 283.4 | 850 | 0.0000 |
| 0.0004 | 300.0 | 900 | 0.0000 |
| 0.0004 | 316.8 | 950 | 0.0000 |
| 0.0004 | 333.4 | 1000 | 0.0000 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1 |