File size: 3,746 Bytes
e669a89 9204289 e669a89 9204289 e669a89 9204289 e669a89 |
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 97 98 99 100 101 102 103 |
---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: cola-pixel-handwritten-mean-vatrpp-256-64-4-5e-5-15000-42
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
type: glue
args: cola
metrics:
- name: Matthews Correlation
type: matthews_correlation
value: 0.07568068132313144
---
<!-- 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. -->
# cola-pixel-handwritten-mean-vatrpp-256-64-4-5e-5-15000-42
This model is a fine-tuned version of [noniewiem/pixel-handwritten](https://huggingface.co/noniewiem/pixel-handwritten) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7009
- Matthews Correlation: 0.0757
## 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: 64
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 15000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.6426 | 3.03 | 100 | 0.6255 | 0.0 |
| 0.6176 | 6.06 | 200 | 0.6308 | 0.0 |
| 0.6183 | 9.09 | 300 | 0.6187 | 0.0 |
| 0.6162 | 12.12 | 400 | 0.6158 | 0.0 |
| 0.614 | 15.15 | 500 | 0.6250 | -0.0293 |
| 0.6096 | 18.18 | 600 | 0.6185 | 0.0 |
| 0.6055 | 21.21 | 700 | 0.6224 | 0.0175 |
| 0.6001 | 24.24 | 800 | 0.6551 | 0.1301 |
| 0.5909 | 27.27 | 900 | 0.6534 | 0.0566 |
| 0.5726 | 30.3 | 1000 | 0.6679 | 0.1029 |
| 0.5524 | 33.33 | 1100 | 0.6901 | 0.0631 |
| 0.5167 | 36.36 | 1200 | 0.7027 | 0.0948 |
| 0.4779 | 39.39 | 1300 | 0.7578 | 0.1012 |
| 0.4271 | 42.42 | 1400 | 0.8021 | 0.1108 |
| 0.3888 | 45.45 | 1500 | 0.8813 | 0.1025 |
| 0.3428 | 48.48 | 1600 | 0.9362 | 0.1437 |
| 0.2977 | 51.51 | 1700 | 1.0786 | 0.1118 |
| 0.2642 | 54.54 | 1800 | 1.0610 | 0.0901 |
| 0.2272 | 57.57 | 1900 | 1.1835 | 0.1155 |
| 0.1915 | 60.6 | 2000 | 1.2531 | 0.1224 |
| 0.1691 | 63.63 | 2100 | 1.3903 | 0.0754 |
| 0.1491 | 66.66 | 2200 | 1.4947 | 0.0674 |
| 0.1339 | 69.69 | 2300 | 1.5434 | 0.0736 |
| 0.1164 | 72.72 | 2400 | 1.5793 | 0.1165 |
| 0.1078 | 75.75 | 2500 | 1.5938 | 0.0995 |
| 0.0974 | 78.78 | 2600 | 1.7009 | 0.0757 |
### Framework versions
- Transformers 4.17.0
- Pytorch 2.3.0+cu121
- Datasets 2.0.0
- Tokenizers 0.13.3
|