File size: 2,318 Bytes
0f113aa |
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 |
---
base_model: StanfordAIMI/RadPhi-2
tags:
- generated_from_trainer
model-index:
- name: outputs_20240325
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. -->
# outputs_20240325
This model is a fine-tuned version of [StanfordAIMI/RadPhi-2](https://huggingface.co/StanfordAIMI/RadPhi-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0816
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 32
- total_train_batch_size: 2048
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 12.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1831 | 0.64 | 25 | 0.1257 |
| 0.1239 | 1.28 | 50 | 0.1044 |
| 0.108 | 1.92 | 75 | 0.0995 |
| 0.0976 | 2.56 | 100 | 0.0978 |
| 0.094 | 3.2 | 125 | 0.0886 |
| 0.0828 | 3.84 | 150 | 0.0893 |
| 0.078 | 4.48 | 175 | 0.0907 |
| 0.0767 | 5.12 | 200 | 0.0866 |
| 0.0697 | 5.76 | 225 | 0.0840 |
| 0.0646 | 6.39 | 250 | 0.0819 |
| 0.0594 | 7.03 | 275 | 0.0795 |
| 0.052 | 7.67 | 300 | 0.0795 |
| 0.0478 | 8.31 | 325 | 0.0803 |
| 0.0447 | 8.95 | 350 | 0.0786 |
| 0.0392 | 9.59 | 375 | 0.0800 |
| 0.038 | 10.23 | 400 | 0.0813 |
| 0.0357 | 10.87 | 425 | 0.0810 |
| 0.035 | 11.51 | 450 | 0.0816 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|