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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- amazon_polarity |
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metrics: |
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- accuracy |
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model-index: |
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- name: amazonPolarity_ELECTRA_5E |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: amazon_polarity |
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type: amazon_polarity |
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config: amazon_polarity |
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split: train |
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args: amazon_polarity |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9333333333333333 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# amazonPolarity_ELECTRA_5E |
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This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the amazon_polarity dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3512 |
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- Accuracy: 0.9333 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.6705 | 0.03 | 50 | 0.5768 | 0.8867 | |
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| 0.4054 | 0.05 | 100 | 0.2968 | 0.8933 | |
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| 0.2461 | 0.08 | 150 | 0.2233 | 0.92 | |
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| 0.1795 | 0.11 | 200 | 0.2265 | 0.9333 | |
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| 0.2293 | 0.13 | 250 | 0.2329 | 0.9267 | |
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| 0.1541 | 0.16 | 300 | 0.2240 | 0.94 | |
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| 0.2006 | 0.19 | 350 | 0.2779 | 0.92 | |
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| 0.1826 | 0.21 | 400 | 0.2765 | 0.9133 | |
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| 0.1935 | 0.24 | 450 | 0.2346 | 0.9333 | |
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| 0.1887 | 0.27 | 500 | 0.2085 | 0.94 | |
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| 0.1688 | 0.29 | 550 | 0.2193 | 0.94 | |
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| 0.1884 | 0.32 | 600 | 0.1982 | 0.9467 | |
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| 0.189 | 0.35 | 650 | 0.1873 | 0.94 | |
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| 0.1564 | 0.37 | 700 | 0.2226 | 0.94 | |
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| 0.1733 | 0.4 | 750 | 0.2462 | 0.9333 | |
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| 0.1436 | 0.43 | 800 | 0.2328 | 0.94 | |
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| 0.1517 | 0.45 | 850 | 0.2128 | 0.9533 | |
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| 0.1922 | 0.48 | 900 | 0.1626 | 0.9467 | |
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| 0.1401 | 0.51 | 950 | 0.2391 | 0.94 | |
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| 0.1606 | 0.53 | 1000 | 0.2001 | 0.94 | |
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| 0.1597 | 0.56 | 1050 | 0.1788 | 0.9467 | |
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| 0.184 | 0.59 | 1100 | 0.1656 | 0.9467 | |
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| 0.1448 | 0.61 | 1150 | 0.1752 | 0.96 | |
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| 0.1575 | 0.64 | 1200 | 0.1878 | 0.9533 | |
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| 0.1836 | 0.67 | 1250 | 0.1416 | 0.9533 | |
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| 0.1378 | 0.69 | 1300 | 0.1866 | 0.9467 | |
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| 0.1901 | 0.72 | 1350 | 0.1654 | 0.9533 | |
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| 0.1697 | 0.75 | 1400 | 0.1720 | 0.9533 | |
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| 0.1624 | 0.77 | 1450 | 0.1700 | 0.9467 | |
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| 0.1487 | 0.8 | 1500 | 0.1786 | 0.94 | |
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| 0.1367 | 0.83 | 1550 | 0.1974 | 0.9267 | |
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| 0.1535 | 0.85 | 1600 | 0.1823 | 0.9267 | |
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| 0.1366 | 0.88 | 1650 | 0.1515 | 0.94 | |
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| 0.1505 | 0.91 | 1700 | 0.1527 | 0.94 | |
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| 0.1554 | 0.93 | 1750 | 0.1855 | 0.9467 | |
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| 0.1478 | 0.96 | 1800 | 0.1885 | 0.9333 | |
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| 0.1603 | 0.99 | 1850 | 0.1990 | 0.9467 | |
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| 0.1637 | 1.01 | 1900 | 0.1901 | 0.9467 | |
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| 0.1074 | 1.04 | 1950 | 0.1886 | 0.9533 | |
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| 0.0874 | 1.07 | 2000 | 0.2399 | 0.94 | |
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| 0.1245 | 1.09 | 2050 | 0.2107 | 0.9467 | |
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| 0.1175 | 1.12 | 2100 | 0.2226 | 0.94 | |
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| 0.1279 | 1.15 | 2150 | 0.2267 | 0.94 | |
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| 0.0947 | 1.17 | 2200 | 0.2342 | 0.94 | |
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| 0.0837 | 1.2 | 2250 | 0.2519 | 0.9467 | |
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| 0.1091 | 1.23 | 2300 | 0.2531 | 0.94 | |
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| 0.0867 | 1.25 | 2350 | 0.2519 | 0.94 | |
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| 0.0845 | 1.28 | 2400 | 0.2431 | 0.9467 | |
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| 0.0836 | 1.31 | 2450 | 0.1936 | 0.9533 | |
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| 0.1633 | 1.33 | 2500 | 0.1875 | 0.9333 | |
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| 0.1029 | 1.36 | 2550 | 0.2345 | 0.94 | |
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| 0.0755 | 1.39 | 2600 | 0.3028 | 0.94 | |
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| 0.1539 | 1.41 | 2650 | 0.2497 | 0.94 | |
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| 0.1055 | 1.44 | 2700 | 0.2002 | 0.9467 | |
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| 0.1234 | 1.47 | 2750 | 0.1763 | 0.9533 | |
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| 0.1312 | 1.49 | 2800 | 0.1998 | 0.94 | |
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| 0.1067 | 1.52 | 2850 | 0.1820 | 0.96 | |
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| 0.1092 | 1.55 | 2900 | 0.1903 | 0.9467 | |
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| 0.1209 | 1.57 | 2950 | 0.1912 | 0.9467 | |
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| 0.0627 | 1.6 | 3000 | 0.2208 | 0.9467 | |
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| 0.1121 | 1.63 | 3050 | 0.2607 | 0.9333 | |
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| 0.1106 | 1.65 | 3100 | 0.1852 | 0.9533 | |
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| 0.0724 | 1.68 | 3150 | 0.2122 | 0.9533 | |
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| 0.1247 | 1.71 | 3200 | 0.2112 | 0.9467 | |
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| 0.1247 | 1.73 | 3250 | 0.2021 | 0.9533 | |
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| 0.096 | 1.76 | 3300 | 0.2340 | 0.9467 | |
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| 0.1056 | 1.79 | 3350 | 0.2165 | 0.94 | |
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| 0.1055 | 1.81 | 3400 | 0.2563 | 0.94 | |
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| 0.1199 | 1.84 | 3450 | 0.2251 | 0.9467 | |
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| 0.0899 | 1.87 | 3500 | 0.1996 | 0.9533 | |
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| 0.109 | 1.89 | 3550 | 0.1924 | 0.9533 | |
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| 0.13 | 1.92 | 3600 | 0.1769 | 0.9467 | |
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| 0.1037 | 1.95 | 3650 | 0.2003 | 0.9533 | |
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| 0.0934 | 1.97 | 3700 | 0.2325 | 0.94 | |
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| 0.1254 | 2.0 | 3750 | 0.2037 | 0.9467 | |
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| 0.0619 | 2.03 | 3800 | 0.2252 | 0.9533 | |
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| 0.093 | 2.05 | 3850 | 0.2145 | 0.9533 | |
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| 0.0827 | 2.08 | 3900 | 0.2237 | 0.9533 | |
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| 0.0679 | 2.11 | 3950 | 0.2643 | 0.9467 | |
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| 0.076 | 2.13 | 4000 | 0.2287 | 0.9533 | |
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| 0.0526 | 2.16 | 4050 | 0.3210 | 0.9267 | |
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| 0.0354 | 2.19 | 4100 | 0.3259 | 0.9333 | |
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| 0.026 | 2.21 | 4150 | 0.3448 | 0.9333 | |
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| 0.0466 | 2.24 | 4200 | 0.3751 | 0.9333 | |
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| 0.043 | 2.27 | 4250 | 0.3122 | 0.9333 | |
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| 0.0521 | 2.29 | 4300 | 0.3155 | 0.9333 | |
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| 0.1018 | 2.32 | 4350 | 0.3066 | 0.94 | |
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| 0.0572 | 2.35 | 4400 | 0.2848 | 0.94 | |
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| 0.0903 | 2.37 | 4450 | 0.2289 | 0.9467 | |
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| 0.0718 | 2.4 | 4500 | 0.2661 | 0.9467 | |
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| 0.0689 | 2.43 | 4550 | 0.2544 | 0.9467 | |
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| 0.0829 | 2.45 | 4600 | 0.2816 | 0.9333 | |
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| 0.0909 | 2.48 | 4650 | 0.2244 | 0.94 | |
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| 0.0888 | 2.51 | 4700 | 0.2620 | 0.94 | |
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| 0.0998 | 2.53 | 4750 | 0.2773 | 0.94 | |
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| 0.0604 | 2.56 | 4800 | 0.2344 | 0.94 | |
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| 0.0619 | 2.59 | 4850 | 0.2551 | 0.9467 | |
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| 0.056 | 2.61 | 4900 | 0.2787 | 0.94 | |
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| 0.1037 | 2.64 | 4950 | 0.2388 | 0.9467 | |
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| 0.0858 | 2.67 | 5000 | 0.2213 | 0.94 | |
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| 0.0674 | 2.69 | 5050 | 0.2339 | 0.9467 | |
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| 0.0438 | 2.72 | 5100 | 0.2759 | 0.9467 | |
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| 0.0615 | 2.75 | 5150 | 0.2739 | 0.9467 | |
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| 0.064 | 2.77 | 5200 | 0.2488 | 0.9467 | |
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| 0.0824 | 2.8 | 5250 | 0.2590 | 0.9467 | |
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| 0.074 | 2.83 | 5300 | 0.2314 | 0.9467 | |
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| 0.1077 | 2.85 | 5350 | 0.2571 | 0.9467 | |
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| 0.0482 | 2.88 | 5400 | 0.2678 | 0.9467 | |
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| 0.0732 | 2.91 | 5450 | 0.2626 | 0.9333 | |
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| 0.0564 | 2.93 | 5500 | 0.2586 | 0.94 | |
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| 0.1019 | 2.96 | 5550 | 0.2706 | 0.9333 | |
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| 0.0675 | 2.99 | 5600 | 0.2568 | 0.9267 | |
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| 0.056 | 3.01 | 5650 | 0.2881 | 0.9333 | |
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| 0.0266 | 3.04 | 5700 | 0.2789 | 0.9467 | |
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| 0.0207 | 3.07 | 5750 | 0.2535 | 0.9467 | |
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| 0.0246 | 3.09 | 5800 | 0.2597 | 0.9467 | |
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| 0.0631 | 3.12 | 5850 | 0.2403 | 0.9533 | |
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| 0.0627 | 3.15 | 5900 | 0.2336 | 0.9533 | |
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| 0.1061 | 3.17 | 5950 | 0.2773 | 0.94 | |
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| 0.0257 | 3.2 | 6000 | 0.2587 | 0.9467 | |
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| 0.0375 | 3.23 | 6050 | 0.2560 | 0.9467 | |
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| 0.0404 | 3.25 | 6100 | 0.2851 | 0.94 | |
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| 0.0748 | 3.28 | 6150 | 0.3005 | 0.94 | |
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| 0.0384 | 3.31 | 6200 | 0.2442 | 0.9533 | |
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| 0.0426 | 3.33 | 6250 | 0.2618 | 0.9533 | |
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| 0.0611 | 3.36 | 6300 | 0.2710 | 0.9467 | |
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| 0.0282 | 3.39 | 6350 | 0.3200 | 0.94 | |
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| 0.0449 | 3.41 | 6400 | 0.3203 | 0.94 | |
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| 0.0508 | 3.44 | 6450 | 0.3197 | 0.94 | |
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| 0.0385 | 3.47 | 6500 | 0.3391 | 0.9333 | |
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| 0.0458 | 3.49 | 6550 | 0.3450 | 0.9333 | |
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| 0.0245 | 3.52 | 6600 | 0.3737 | 0.9333 | |
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| 0.0547 | 3.55 | 6650 | 0.2889 | 0.94 | |
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| 0.0398 | 3.57 | 6700 | 0.3751 | 0.9333 | |
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| 0.0497 | 3.6 | 6750 | 0.2748 | 0.9467 | |
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| 0.0466 | 3.63 | 6800 | 0.3438 | 0.9333 | |
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| 0.0241 | 3.65 | 6850 | 0.3279 | 0.9267 | |
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| 0.0631 | 3.68 | 6900 | 0.2921 | 0.94 | |
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| 0.0256 | 3.71 | 6950 | 0.3595 | 0.9267 | |
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| 0.0615 | 3.73 | 7000 | 0.3190 | 0.9333 | |
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| 0.0495 | 3.76 | 7050 | 0.3451 | 0.9267 | |
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| 0.0519 | 3.79 | 7100 | 0.3303 | 0.9333 | |
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| 0.0243 | 3.81 | 7150 | 0.3344 | 0.9333 | |
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| 0.0348 | 3.84 | 7200 | 0.3609 | 0.9333 | |
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| 0.0542 | 3.87 | 7250 | 0.2797 | 0.9333 | |
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| 0.0791 | 3.89 | 7300 | 0.2504 | 0.94 | |
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| 0.0272 | 3.92 | 7350 | 0.3165 | 0.9333 | |
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| 0.0701 | 3.95 | 7400 | 0.3039 | 0.9333 | |
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| 0.0866 | 3.97 | 7450 | 0.3233 | 0.9267 | |
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| 0.0461 | 4.0 | 7500 | 0.3114 | 0.9267 | |
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| 0.0486 | 4.03 | 7550 | 0.2995 | 0.94 | |
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| 0.0052 | 4.05 | 7600 | 0.3128 | 0.94 | |
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| 0.0312 | 4.08 | 7650 | 0.3723 | 0.9333 | |
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| 0.0277 | 4.11 | 7700 | 0.3158 | 0.94 | |
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| 0.0407 | 4.13 | 7750 | 0.3187 | 0.94 | |
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| 0.0224 | 4.16 | 7800 | 0.3258 | 0.9333 | |
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| 0.0335 | 4.19 | 7850 | 0.3539 | 0.9333 | |
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| 0.0425 | 4.21 | 7900 | 0.3391 | 0.9333 | |
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| 0.0394 | 4.24 | 7950 | 0.3470 | 0.9333 | |
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| 0.015 | 4.27 | 8000 | 0.3680 | 0.9333 | |
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| 0.0166 | 4.29 | 8050 | 0.3689 | 0.9333 | |
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| 0.0358 | 4.32 | 8100 | 0.3281 | 0.94 | |
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| 0.0152 | 4.35 | 8150 | 0.3391 | 0.9333 | |
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| 0.0235 | 4.37 | 8200 | 0.3506 | 0.94 | |
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| 0.0357 | 4.4 | 8250 | 0.3549 | 0.94 | |
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| 0.0153 | 4.43 | 8300 | 0.3564 | 0.94 | |
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| 0.0366 | 4.45 | 8350 | 0.3836 | 0.9333 | |
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| 0.0381 | 4.48 | 8400 | 0.3428 | 0.9333 | |
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| 0.0349 | 4.51 | 8450 | 0.3600 | 0.94 | |
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| 0.028 | 4.53 | 8500 | 0.3592 | 0.9333 | |
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| 0.0322 | 4.56 | 8550 | 0.3478 | 0.9333 | |
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| 0.0237 | 4.59 | 8600 | 0.3636 | 0.94 | |
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| 0.0398 | 4.61 | 8650 | 0.3433 | 0.9333 | |
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| 0.062 | 4.64 | 8700 | 0.3158 | 0.94 | |
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| 0.0148 | 4.67 | 8750 | 0.3435 | 0.9333 | |
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| 0.0197 | 4.69 | 8800 | 0.3394 | 0.9333 | |
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| 0.0594 | 4.72 | 8850 | 0.3336 | 0.9333 | |
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| 0.0426 | 4.75 | 8900 | 0.3351 | 0.9333 | |
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| 0.003 | 4.77 | 8950 | 0.3479 | 0.9333 | |
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| 0.0268 | 4.8 | 9000 | 0.3479 | 0.9333 | |
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| 0.0524 | 4.83 | 9050 | 0.3485 | 0.9333 | |
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| 0.0259 | 4.85 | 9100 | 0.3501 | 0.9333 | |
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| 0.0326 | 4.88 | 9150 | 0.3498 | 0.9333 | |
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| 0.0236 | 4.91 | 9200 | 0.3482 | 0.9333 | |
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| 0.0209 | 4.93 | 9250 | 0.3504 | 0.9333 | |
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| 0.0366 | 4.96 | 9300 | 0.3503 | 0.9333 | |
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| 0.0246 | 4.99 | 9350 | 0.3512 | 0.9333 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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