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README.md
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| 1 |
+
---
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| 2 |
+
license: mit
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| 3 |
+
tags:
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| 4 |
+
- generated_from_trainer
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| 5 |
+
datasets:
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| 6 |
+
- yelp_review_full
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| 7 |
+
metrics:
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| 8 |
+
- accuracy
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| 9 |
+
model-index:
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| 10 |
+
- name: YELP_roBERTa_5E
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| 11 |
+
results:
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| 12 |
+
- task:
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| 13 |
+
name: Text Classification
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| 14 |
+
type: text-classification
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| 15 |
+
dataset:
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| 16 |
+
name: yelp_review_full
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| 17 |
+
type: yelp_review_full
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| 18 |
+
config: yelp_review_full
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| 19 |
+
split: train
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| 20 |
+
args: yelp_review_full
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| 21 |
+
metrics:
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| 22 |
+
- name: Accuracy
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| 23 |
+
type: accuracy
|
| 24 |
+
value: 0.9866666666666667
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| 25 |
+
---
|
| 26 |
+
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| 27 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 28 |
+
should probably proofread and complete it, then remove this comment. -->
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| 29 |
+
|
| 30 |
+
# YELP_roBERTa_5E
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| 31 |
+
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| 32 |
+
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the yelp_review_full dataset.
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| 33 |
+
It achieves the following results on the evaluation set:
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| 34 |
+
- Loss: 0.0995
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| 35 |
+
- Accuracy: 0.9867
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| 36 |
+
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| 37 |
+
## Model description
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| 38 |
+
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| 39 |
+
More information needed
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| 40 |
+
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| 41 |
+
## Intended uses & limitations
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| 42 |
+
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| 43 |
+
More information needed
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| 44 |
+
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| 45 |
+
## Training and evaluation data
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| 46 |
+
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| 47 |
+
More information needed
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| 48 |
+
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| 49 |
+
## Training procedure
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| 50 |
+
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| 51 |
+
### Training hyperparameters
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| 52 |
+
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| 53 |
+
The following hyperparameters were used during training:
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| 54 |
+
- learning_rate: 1e-05
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| 55 |
+
- train_batch_size: 16
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| 56 |
+
- eval_batch_size: 8
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| 57 |
+
- seed: 42
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| 58 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| 59 |
+
- lr_scheduler_type: linear
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| 60 |
+
- num_epochs: 5
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| 61 |
+
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| 62 |
+
### Training results
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| 63 |
+
|
| 64 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 65 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 66 |
+
| 0.5721 | 0.03 | 50 | 0.3248 | 0.88 |
|
| 67 |
+
| 0.2836 | 0.06 | 100 | 0.1190 | 0.9733 |
|
| 68 |
+
| 0.1793 | 0.1 | 150 | 0.1707 | 0.96 |
|
| 69 |
+
| 0.2196 | 0.13 | 200 | 0.0841 | 0.9733 |
|
| 70 |
+
| 0.2102 | 0.16 | 250 | 0.0634 | 0.9867 |
|
| 71 |
+
| 0.2197 | 0.19 | 300 | 0.0763 | 0.98 |
|
| 72 |
+
| 0.1866 | 0.22 | 350 | 0.0640 | 0.9867 |
|
| 73 |
+
| 0.1717 | 0.26 | 400 | 0.0612 | 0.9867 |
|
| 74 |
+
| 0.1443 | 0.29 | 450 | 0.0844 | 0.9733 |
|
| 75 |
+
| 0.1669 | 0.32 | 500 | 0.1297 | 0.9667 |
|
| 76 |
+
| 0.2005 | 0.35 | 550 | 0.0644 | 0.9867 |
|
| 77 |
+
| 0.1543 | 0.38 | 600 | 0.0874 | 0.9867 |
|
| 78 |
+
| 0.1345 | 0.42 | 650 | 0.1853 | 0.96 |
|
| 79 |
+
| 0.1664 | 0.45 | 700 | 0.1157 | 0.9667 |
|
| 80 |
+
| 0.1876 | 0.48 | 750 | 0.0474 | 0.9733 |
|
| 81 |
+
| 0.111 | 0.51 | 800 | 0.0645 | 0.98 |
|
| 82 |
+
| 0.1511 | 0.54 | 850 | 0.0432 | 0.9933 |
|
| 83 |
+
| 0.1846 | 0.58 | 900 | 0.0505 | 0.9867 |
|
| 84 |
+
| 0.151 | 0.61 | 950 | 0.0452 | 0.98 |
|
| 85 |
+
| 0.1338 | 0.64 | 1000 | 0.1007 | 0.98 |
|
| 86 |
+
| 0.1175 | 0.67 | 1050 | 0.0747 | 0.9867 |
|
| 87 |
+
| 0.1818 | 0.7 | 1100 | 0.0852 | 0.98 |
|
| 88 |
+
| 0.1557 | 0.74 | 1150 | 0.0255 | 0.9933 |
|
| 89 |
+
| 0.1487 | 0.77 | 1200 | 0.1266 | 0.9733 |
|
| 90 |
+
| 0.1315 | 0.8 | 1250 | 0.0593 | 0.9867 |
|
| 91 |
+
| 0.1059 | 0.83 | 1300 | 0.0697 | 0.9867 |
|
| 92 |
+
| 0.108 | 0.86 | 1350 | 0.0459 | 0.9933 |
|
| 93 |
+
| 0.1525 | 0.9 | 1400 | 0.0446 | 0.9933 |
|
| 94 |
+
| 0.1185 | 0.93 | 1450 | 0.0528 | 0.9867 |
|
| 95 |
+
| 0.1611 | 0.96 | 1500 | 0.0582 | 0.9867 |
|
| 96 |
+
| 0.1556 | 0.99 | 1550 | 0.0726 | 0.98 |
|
| 97 |
+
| 0.0902 | 1.02 | 1600 | 0.0466 | 0.9867 |
|
| 98 |
+
| 0.1535 | 1.06 | 1650 | 0.0850 | 0.9733 |
|
| 99 |
+
| 0.0787 | 1.09 | 1700 | 0.0869 | 0.9867 |
|
| 100 |
+
| 0.1019 | 1.12 | 1750 | 0.0984 | 0.98 |
|
| 101 |
+
| 0.1234 | 1.15 | 1800 | 0.0358 | 0.9933 |
|
| 102 |
+
| 0.0884 | 1.18 | 1850 | 0.0621 | 0.9867 |
|
| 103 |
+
| 0.0785 | 1.22 | 1900 | 0.0507 | 0.9867 |
|
| 104 |
+
| 0.1454 | 1.25 | 1950 | 0.0793 | 0.98 |
|
| 105 |
+
| 0.1035 | 1.28 | 2000 | 0.0501 | 0.9867 |
|
| 106 |
+
| 0.0579 | 1.31 | 2050 | 0.0935 | 0.9867 |
|
| 107 |
+
| 0.1215 | 1.34 | 2100 | 0.0079 | 1.0 |
|
| 108 |
+
| 0.0958 | 1.38 | 2150 | 0.0673 | 0.9867 |
|
| 109 |
+
| 0.106 | 1.41 | 2200 | 0.0875 | 0.9867 |
|
| 110 |
+
| 0.095 | 1.44 | 2250 | 0.0745 | 0.9867 |
|
| 111 |
+
| 0.0958 | 1.47 | 2300 | 0.0715 | 0.9867 |
|
| 112 |
+
| 0.085 | 1.5 | 2350 | 0.0742 | 0.9867 |
|
| 113 |
+
| 0.082 | 1.54 | 2400 | 0.1053 | 0.9733 |
|
| 114 |
+
| 0.1202 | 1.57 | 2450 | 0.0711 | 0.9867 |
|
| 115 |
+
| 0.1041 | 1.6 | 2500 | 0.0723 | 0.9867 |
|
| 116 |
+
| 0.1145 | 1.63 | 2550 | 0.0361 | 0.9867 |
|
| 117 |
+
| 0.0909 | 1.66 | 2600 | 0.0868 | 0.9867 |
|
| 118 |
+
| 0.1029 | 1.7 | 2650 | 0.0680 | 0.9867 |
|
| 119 |
+
| 0.1083 | 1.73 | 2700 | 0.0599 | 0.9867 |
|
| 120 |
+
| 0.0871 | 1.76 | 2750 | 0.0452 | 0.9867 |
|
| 121 |
+
| 0.1506 | 1.79 | 2800 | 0.0344 | 0.9933 |
|
| 122 |
+
| 0.0778 | 1.82 | 2850 | 0.0380 | 0.9933 |
|
| 123 |
+
| 0.0982 | 1.86 | 2900 | 0.0349 | 0.9933 |
|
| 124 |
+
| 0.1296 | 1.89 | 2950 | 0.0713 | 0.9867 |
|
| 125 |
+
| 0.0836 | 1.92 | 3000 | 0.0693 | 0.9867 |
|
| 126 |
+
| 0.0699 | 1.95 | 3050 | 0.1023 | 0.98 |
|
| 127 |
+
| 0.0631 | 1.98 | 3100 | 0.0852 | 0.98 |
|
| 128 |
+
| 0.0724 | 2.02 | 3150 | 0.0835 | 0.9867 |
|
| 129 |
+
| 0.0898 | 2.05 | 3200 | 0.0872 | 0.9867 |
|
| 130 |
+
| 0.0642 | 2.08 | 3250 | 0.0427 | 0.9933 |
|
| 131 |
+
| 0.0524 | 2.11 | 3300 | 0.0731 | 0.9867 |
|
| 132 |
+
| 0.0415 | 2.14 | 3350 | 0.0632 | 0.9867 |
|
| 133 |
+
| 0.0604 | 2.18 | 3400 | 0.0428 | 0.9867 |
|
| 134 |
+
| 0.0701 | 2.21 | 3450 | 0.0671 | 0.9867 |
|
| 135 |
+
| 0.0668 | 2.24 | 3500 | 0.0360 | 0.9933 |
|
| 136 |
+
| 0.0442 | 2.27 | 3550 | 0.0454 | 0.9933 |
|
| 137 |
+
| 0.0677 | 2.3 | 3600 | 0.0517 | 0.9867 |
|
| 138 |
+
| 0.0965 | 2.34 | 3650 | 0.0659 | 0.98 |
|
| 139 |
+
| 0.0781 | 2.37 | 3700 | 0.0732 | 0.9867 |
|
| 140 |
+
| 0.0421 | 2.4 | 3750 | 0.0855 | 0.9867 |
|
| 141 |
+
| 0.0674 | 2.43 | 3800 | 0.0813 | 0.9867 |
|
| 142 |
+
| 0.0613 | 2.46 | 3850 | 0.0859 | 0.98 |
|
| 143 |
+
| 0.0679 | 2.5 | 3900 | 0.0721 | 0.9867 |
|
| 144 |
+
| 0.0417 | 2.53 | 3950 | 0.0977 | 0.9867 |
|
| 145 |
+
| 0.0616 | 2.56 | 4000 | 0.0789 | 0.9867 |
|
| 146 |
+
| 0.0678 | 2.59 | 4050 | 0.0804 | 0.9867 |
|
| 147 |
+
| 0.0651 | 2.62 | 4100 | 0.0994 | 0.98 |
|
| 148 |
+
| 0.0714 | 2.66 | 4150 | 0.0744 | 0.98 |
|
| 149 |
+
| 0.034 | 2.69 | 4200 | 0.0679 | 0.9867 |
|
| 150 |
+
| 0.0356 | 2.72 | 4250 | 0.0432 | 0.9933 |
|
| 151 |
+
| 0.0813 | 2.75 | 4300 | 0.0483 | 0.9933 |
|
| 152 |
+
| 0.052 | 2.78 | 4350 | 0.0689 | 0.9867 |
|
| 153 |
+
| 0.0611 | 2.82 | 4400 | 0.0474 | 0.9867 |
|
| 154 |
+
| 0.0615 | 2.85 | 4450 | 0.0557 | 0.9867 |
|
| 155 |
+
| 0.0569 | 2.88 | 4500 | 0.1056 | 0.98 |
|
| 156 |
+
| 0.0352 | 2.91 | 4550 | 0.0443 | 0.9933 |
|
| 157 |
+
| 0.0312 | 2.94 | 4600 | 0.1026 | 0.98 |
|
| 158 |
+
| 0.0662 | 2.98 | 4650 | 0.0677 | 0.9867 |
|
| 159 |
+
| 0.0694 | 3.01 | 4700 | 0.0368 | 0.9933 |
|
| 160 |
+
| 0.0144 | 3.04 | 4750 | 0.0647 | 0.9867 |
|
| 161 |
+
| 0.0378 | 3.07 | 4800 | 0.0893 | 0.9867 |
|
| 162 |
+
| 0.0393 | 3.1 | 4850 | 0.0841 | 0.9867 |
|
| 163 |
+
| 0.0598 | 3.13 | 4900 | 0.0594 | 0.9867 |
|
| 164 |
+
| 0.0329 | 3.17 | 4950 | 0.0933 | 0.9867 |
|
| 165 |
+
| 0.036 | 3.2 | 5000 | 0.0974 | 0.9867 |
|
| 166 |
+
| 0.0166 | 3.23 | 5050 | 0.0962 | 0.9867 |
|
| 167 |
+
| 0.0189 | 3.26 | 5100 | 0.0827 | 0.9867 |
|
| 168 |
+
| 0.0482 | 3.29 | 5150 | 0.0955 | 0.9867 |
|
| 169 |
+
| 0.0105 | 3.33 | 5200 | 0.0745 | 0.9867 |
|
| 170 |
+
| 0.0447 | 3.36 | 5250 | 0.1038 | 0.9867 |
|
| 171 |
+
| 0.0495 | 3.39 | 5300 | 0.0684 | 0.9867 |
|
| 172 |
+
| 0.0445 | 3.42 | 5350 | 0.0815 | 0.9867 |
|
| 173 |
+
| 0.0006 | 3.45 | 5400 | 0.1012 | 0.9867 |
|
| 174 |
+
| 0.0214 | 3.49 | 5450 | 0.0707 | 0.9867 |
|
| 175 |
+
| 0.0289 | 3.52 | 5500 | 0.1000 | 0.9867 |
|
| 176 |
+
| 0.0304 | 3.55 | 5550 | 0.1069 | 0.9867 |
|
| 177 |
+
| 0.0339 | 3.58 | 5600 | 0.1079 | 0.9867 |
|
| 178 |
+
| 0.0227 | 3.61 | 5650 | 0.1032 | 0.9867 |
|
| 179 |
+
| 0.0626 | 3.65 | 5700 | 0.0978 | 0.9867 |
|
| 180 |
+
| 0.04 | 3.68 | 5750 | 0.0965 | 0.9867 |
|
| 181 |
+
| 0.0358 | 3.71 | 5800 | 0.1048 | 0.9867 |
|
| 182 |
+
| 0.0287 | 3.74 | 5850 | 0.0921 | 0.9867 |
|
| 183 |
+
| 0.049 | 3.77 | 5900 | 0.1108 | 0.98 |
|
| 184 |
+
| 0.0497 | 3.81 | 5950 | 0.0795 | 0.9867 |
|
| 185 |
+
| 0.0047 | 3.84 | 6000 | 0.0979 | 0.9867 |
|
| 186 |
+
| 0.0252 | 3.87 | 6050 | 0.1071 | 0.9867 |
|
| 187 |
+
| 0.0691 | 3.9 | 6100 | 0.0821 | 0.9867 |
|
| 188 |
+
| 0.0419 | 3.93 | 6150 | 0.0896 | 0.9867 |
|
| 189 |
+
| 0.0197 | 3.97 | 6200 | 0.0943 | 0.9867 |
|
| 190 |
+
| 0.0281 | 4.0 | 6250 | 0.0901 | 0.9867 |
|
| 191 |
+
| 0.0118 | 4.03 | 6300 | 0.0950 | 0.9867 |
|
| 192 |
+
| 0.0057 | 4.06 | 6350 | 0.1031 | 0.9867 |
|
| 193 |
+
| 0.0335 | 4.09 | 6400 | 0.0896 | 0.9867 |
|
| 194 |
+
| 0.0095 | 4.13 | 6450 | 0.0966 | 0.9867 |
|
| 195 |
+
| 0.05 | 4.16 | 6500 | 0.0977 | 0.9867 |
|
| 196 |
+
| 0.0142 | 4.19 | 6550 | 0.1174 | 0.98 |
|
| 197 |
+
| 0.018 | 4.22 | 6600 | 0.0963 | 0.9867 |
|
| 198 |
+
| 0.0274 | 4.25 | 6650 | 0.0953 | 0.9867 |
|
| 199 |
+
| 0.0199 | 4.29 | 6700 | 0.0968 | 0.9867 |
|
| 200 |
+
| 0.0171 | 4.32 | 6750 | 0.0963 | 0.9867 |
|
| 201 |
+
| 0.0195 | 4.35 | 6800 | 0.0916 | 0.9867 |
|
| 202 |
+
| 0.0091 | 4.38 | 6850 | 0.0954 | 0.9867 |
|
| 203 |
+
| 0.0115 | 4.41 | 6900 | 0.0974 | 0.9867 |
|
| 204 |
+
| 0.0299 | 4.45 | 6950 | 0.0971 | 0.9867 |
|
| 205 |
+
| 0.0338 | 4.48 | 7000 | 0.0922 | 0.9867 |
|
| 206 |
+
| 0.0107 | 4.51 | 7050 | 0.0964 | 0.9867 |
|
| 207 |
+
| 0.0063 | 4.54 | 7100 | 0.0921 | 0.9867 |
|
| 208 |
+
| 0.0099 | 4.57 | 7150 | 0.0923 | 0.9867 |
|
| 209 |
+
| 0.0101 | 4.61 | 7200 | 0.0971 | 0.9867 |
|
| 210 |
+
| 0.0262 | 4.64 | 7250 | 0.1008 | 0.9867 |
|
| 211 |
+
| 0.0097 | 4.67 | 7300 | 0.0999 | 0.9867 |
|
| 212 |
+
| 0.0302 | 4.7 | 7350 | 0.0980 | 0.9867 |
|
| 213 |
+
| 0.0225 | 4.73 | 7400 | 0.0976 | 0.9867 |
|
| 214 |
+
| 0.0235 | 4.77 | 7450 | 0.1016 | 0.9867 |
|
| 215 |
+
| 0.0106 | 4.8 | 7500 | 0.1034 | 0.9867 |
|
| 216 |
+
| 0.0495 | 4.83 | 7550 | 0.1135 | 0.98 |
|
| 217 |
+
| 0.0228 | 4.86 | 7600 | 0.1034 | 0.9867 |
|
| 218 |
+
| 0.0229 | 4.89 | 7650 | 0.0990 | 0.9867 |
|
| 219 |
+
| 0.0206 | 4.93 | 7700 | 0.0993 | 0.9867 |
|
| 220 |
+
| 0.0188 | 4.96 | 7750 | 0.0993 | 0.9867 |
|
| 221 |
+
| 0.0189 | 4.99 | 7800 | 0.0995 | 0.9867 |
|
| 222 |
+
|
| 223 |
+
|
| 224 |
+
### Framework versions
|
| 225 |
+
|
| 226 |
+
- Transformers 4.24.0
|
| 227 |
+
- Pytorch 1.13.0
|
| 228 |
+
- Datasets 2.3.2
|
| 229 |
+
- Tokenizers 0.13.2
|