File size: 3,307 Bytes
105c559 |
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 89 90 91 92 93 94 95 96 |
---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
model-index:
- name: CS505-Classifier-T4_predictLabel_a1_v5
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_v5
This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0018
## 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: 5e-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: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 0.98 | 48 | 0.6517 |
| No log | 1.96 | 96 | 0.3227 |
| No log | 2.94 | 144 | 0.2342 |
| No log | 3.92 | 192 | 0.1815 |
| No log | 4.9 | 240 | 0.1703 |
| No log | 5.88 | 288 | 0.1231 |
| No log | 6.86 | 336 | 0.0730 |
| No log | 7.84 | 384 | 0.0803 |
| No log | 8.82 | 432 | 0.0476 |
| No log | 9.8 | 480 | 0.0384 |
| 0.2908 | 10.78 | 528 | 0.0281 |
| 0.2908 | 11.76 | 576 | 0.0329 |
| 0.2908 | 12.73 | 624 | 0.0234 |
| 0.2908 | 13.71 | 672 | 0.0119 |
| 0.2908 | 14.69 | 720 | 0.0101 |
| 0.2908 | 15.67 | 768 | 0.0081 |
| 0.2908 | 16.65 | 816 | 0.0137 |
| 0.2908 | 17.63 | 864 | 0.0075 |
| 0.2908 | 18.61 | 912 | 0.0053 |
| 0.2908 | 19.59 | 960 | 0.0035 |
| 0.0216 | 20.57 | 1008 | 0.0060 |
| 0.0216 | 21.55 | 1056 | 0.0028 |
| 0.0216 | 22.53 | 1104 | 0.0027 |
| 0.0216 | 23.51 | 1152 | 0.0026 |
| 0.0216 | 24.49 | 1200 | 0.0024 |
| 0.0216 | 25.47 | 1248 | 0.0023 |
| 0.0216 | 26.45 | 1296 | 0.0022 |
| 0.0216 | 27.43 | 1344 | 0.0022 |
| 0.0216 | 28.41 | 1392 | 0.0021 |
| 0.0216 | 29.39 | 1440 | 0.0020 |
| 0.0216 | 30.37 | 1488 | 0.0021 |
| 0.0043 | 31.35 | 1536 | 0.0020 |
| 0.0043 | 32.33 | 1584 | 0.0019 |
| 0.0043 | 33.31 | 1632 | 0.0019 |
| 0.0043 | 34.29 | 1680 | 0.0019 |
| 0.0043 | 35.27 | 1728 | 0.0019 |
| 0.0043 | 36.24 | 1776 | 0.0019 |
| 0.0043 | 37.22 | 1824 | 0.0019 |
| 0.0043 | 38.2 | 1872 | 0.0018 |
| 0.0043 | 39.18 | 1920 | 0.0018 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|