File size: 3,201 Bytes
b5e618e |
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 83 84 85 86 87 88 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Finetuned_FLAN-T5_VALUE_finetuning_lr3e-4
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. -->
# Finetuned_FLAN-T5_VALUE_finetuning_lr3e-4
This model is a fine-tuned version of [liuyanchen1015/FLAN-T5_GLUE_finetuning_lr3e-4](https://huggingface.co/liuyanchen1015/FLAN-T5_GLUE_finetuning_lr3e-4) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1268
- Accuracy: 0.8823
## 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: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.06 | 0.17 | 2500 | 0.0907 | 0.8692 |
| 0.0623 | 0.34 | 5000 | 0.0920 | 0.8698 |
| 0.0629 | 0.51 | 7500 | 0.0875 | 0.8701 |
| 0.0641 | 0.68 | 10000 | 0.0892 | 0.8709 |
| 0.0634 | 0.85 | 12500 | 0.0908 | 0.8696 |
| 0.0627 | 1.02 | 15000 | 0.0939 | 0.8723 |
| 0.0467 | 1.18 | 17500 | 0.0949 | 0.8738 |
| 0.0485 | 1.35 | 20000 | 0.0954 | 0.8731 |
| 0.0496 | 1.52 | 22500 | 0.0909 | 0.8729 |
| 0.0497 | 1.69 | 25000 | 0.0942 | 0.8765 |
| 0.0509 | 1.86 | 27500 | 0.0925 | 0.8753 |
| 0.047 | 2.03 | 30000 | 0.1024 | 0.8781 |
| 0.0346 | 2.2 | 32500 | 0.1011 | 0.8791 |
| 0.0364 | 2.37 | 35000 | 0.1013 | 0.8773 |
| 0.0359 | 2.54 | 37500 | 0.1013 | 0.8785 |
| 0.0374 | 2.71 | 40000 | 0.1002 | 0.8785 |
| 0.0367 | 2.88 | 42500 | 0.1015 | 0.8787 |
| 0.0338 | 3.05 | 45000 | 0.1199 | 0.8779 |
| 0.0253 | 3.22 | 47500 | 0.1191 | 0.8791 |
| 0.0256 | 3.38 | 50000 | 0.1165 | 0.8787 |
| 0.0257 | 3.55 | 52500 | 0.1136 | 0.88 |
| 0.0265 | 3.72 | 55000 | 0.1092 | 0.881 |
| 0.026 | 3.89 | 57500 | 0.1131 | 0.8814 |
| 0.0233 | 4.06 | 60000 | 0.1270 | 0.8798 |
| 0.018 | 4.23 | 62500 | 0.1291 | 0.8808 |
| 0.0191 | 4.4 | 65000 | 0.1269 | 0.8814 |
| 0.0191 | 4.57 | 67500 | 0.1279 | 0.8816 |
| 0.0186 | 4.74 | 70000 | 0.1264 | 0.8824 |
| 0.0184 | 4.91 | 72500 | 0.1268 | 0.8823 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0+cu117
- Datasets 2.10.1
- Tokenizers 0.12.1
|