File size: 2,272 Bytes
04ba4c0 1e4c9a6 04ba4c0 1e4c9a6 04ba4c0 1e4c9a6 04ba4c0 |
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 |
---
base_model: vinai/phobert-base
tags:
- generated_from_trainer
model-index:
- name: CS505-Classifier-T4_predictLabel_a1
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. -->
# CS505-Classifier-T4_predictLabel_a1
This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0155
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 0.98 | 48 | 1.0473 |
| No log | 1.96 | 96 | 0.5664 |
| No log | 2.94 | 144 | 0.3371 |
| No log | 3.92 | 192 | 0.2277 |
| No log | 4.9 | 240 | 0.1850 |
| No log | 5.88 | 288 | 0.1451 |
| No log | 6.86 | 336 | 0.1126 |
| No log | 7.84 | 384 | 0.0853 |
| No log | 8.82 | 432 | 0.0635 |
| No log | 9.8 | 480 | 0.0598 |
| 0.4029 | 10.78 | 528 | 0.0407 |
| 0.4029 | 11.76 | 576 | 0.0337 |
| 0.4029 | 12.73 | 624 | 0.0300 |
| 0.4029 | 13.71 | 672 | 0.0270 |
| 0.4029 | 14.69 | 720 | 0.0209 |
| 0.4029 | 15.67 | 768 | 0.0196 |
| 0.4029 | 16.65 | 816 | 0.0205 |
| 0.4029 | 17.63 | 864 | 0.0181 |
| 0.4029 | 18.61 | 912 | 0.0160 |
| 0.4029 | 19.59 | 960 | 0.0155 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|