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--- |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: ashishbaraiya/my-tweets-finetuned |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# ashishbaraiya/my-tweets-finetuned |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0656 |
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- Validation Loss: 3.2945 |
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- Epoch: 98 |
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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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- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 4500, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 9.3483 | 8.3624 | 0 | |
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| 7.2778 | 6.9685 | 1 | |
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| 5.9195 | 6.2234 | 2 | |
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| 5.0730 | 5.6830 | 3 | |
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| 4.4703 | 5.3916 | 4 | |
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| 3.8427 | 4.8847 | 5 | |
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| 3.3641 | 4.5318 | 6 | |
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| 2.8373 | 4.3084 | 7 | |
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| 2.4261 | 4.0802 | 8 | |
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| 2.0691 | 3.8920 | 9 | |
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| 1.8213 | 3.8208 | 10 | |
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| 1.5922 | 3.6103 | 11 | |
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| 1.3694 | 3.5038 | 12 | |
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| 1.1764 | 3.3149 | 13 | |
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| 1.0135 | 3.2981 | 14 | |
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| 0.8874 | 3.2975 | 15 | |
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| 0.7716 | 3.2103 | 16 | |
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| 0.6679 | 3.3297 | 17 | |
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| 0.5770 | 3.2517 | 18 | |
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| 0.5098 | 3.0959 | 19 | |
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| 0.4403 | 3.1526 | 20 | |
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| 0.3791 | 2.9750 | 21 | |
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| 0.3367 | 3.0588 | 22 | |
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| 0.3027 | 3.0408 | 23 | |
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| 0.2617 | 3.1930 | 24 | |
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| 0.2387 | 3.1227 | 25 | |
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| 0.2175 | 3.0582 | 26 | |
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| 0.2062 | 3.1239 | 27 | |
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| 0.1868 | 3.0407 | 28 | |
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| 0.1746 | 3.2357 | 29 | |
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| 0.1657 | 3.1285 | 30 | |
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| 0.1536 | 3.2110 | 31 | |
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| 0.1512 | 3.1890 | 32 | |
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| 0.1447 | 3.1713 | 33 | |
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| 0.1426 | 3.1498 | 34 | |
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| 0.1369 | 3.1877 | 35 | |
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| 0.1327 | 3.2019 | 36 | |
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| 0.1303 | 3.0486 | 37 | |
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| 0.1213 | 3.1264 | 38 | |
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| 0.1204 | 3.1468 | 39 | |
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| 0.1206 | 3.1846 | 40 | |
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| 0.1125 | 3.1880 | 41 | |
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| 0.1113 | 3.1980 | 42 | |
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| 0.1098 | 3.1759 | 43 | |
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| 0.1071 | 3.1385 | 44 | |
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| 0.1055 | 3.1730 | 45 | |
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| 0.1024 | 3.1820 | 46 | |
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| 0.0995 | 3.1252 | 47 | |
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| 0.0995 | 3.1279 | 48 | |
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| 0.1004 | 3.2428 | 49 | |
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| 0.0982 | 3.1116 | 50 | |
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| 0.0957 | 3.2210 | 51 | |
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| 0.0936 | 3.1351 | 52 | |
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| 0.0917 | 3.1618 | 53 | |
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| 0.0930 | 3.1924 | 54 | |
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| 0.0929 | 3.2831 | 55 | |
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| 0.0889 | 3.2458 | 56 | |
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| 0.0913 | 3.2061 | 57 | |
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| 0.0899 | 3.4128 | 58 | |
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| 0.0880 | 3.2114 | 59 | |
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| 0.0869 | 3.2738 | 60 | |
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| 0.0878 | 3.1723 | 61 | |
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| 0.0844 | 3.1465 | 62 | |
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| 0.0846 | 3.1106 | 63 | |
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| 0.0841 | 3.2216 | 64 | |
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| 0.0824 | 3.2971 | 65 | |
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| 0.0823 | 3.2267 | 66 | |
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| 0.0811 | 3.2503 | 67 | |
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| 0.0823 | 3.1981 | 68 | |
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| 0.0808 | 3.2618 | 69 | |
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| 0.0803 | 3.1607 | 70 | |
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| 0.0786 | 3.3295 | 71 | |
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| 0.0801 | 3.2952 | 72 | |
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| 0.0777 | 3.2545 | 73 | |
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| 0.0764 | 3.1248 | 74 | |
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| 0.0772 | 3.2185 | 75 | |
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| 0.0758 | 3.3147 | 76 | |
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| 0.0764 | 3.1842 | 77 | |
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| 0.0758 | 3.2346 | 78 | |
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| 0.0739 | 3.2914 | 79 | |
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| 0.0738 | 3.2163 | 80 | |
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| 0.0738 | 3.3555 | 81 | |
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| 0.0731 | 3.0948 | 82 | |
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| 0.0726 | 3.2040 | 83 | |
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| 0.0729 | 3.2187 | 84 | |
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| 0.0709 | 3.2877 | 85 | |
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| 0.0703 | 3.3668 | 86 | |
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| 0.0709 | 3.2290 | 87 | |
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| 0.0712 | 3.3148 | 88 | |
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| 0.0697 | 3.2762 | 89 | |
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| 0.0694 | 3.2083 | 90 | |
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| 0.0688 | 3.2673 | 91 | |
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| 0.0694 | 3.2816 | 92 | |
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| 0.0683 | 3.3135 | 93 | |
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| 0.0680 | 3.2971 | 94 | |
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| 0.0681 | 3.2272 | 95 | |
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| 0.0670 | 3.2317 | 96 | |
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| 0.0662 | 3.2029 | 97 | |
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| 0.0656 | 3.2945 | 98 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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