Upload 12 files
Browse filesupload model and results
- .gitattributes +1 -0
- all_results.json +20 -0
- config.json +41 -0
- eval_results.json +9 -0
- predict_results.json +8 -0
- predictions.txt +5011 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +15 -0
- tokenizer.json +3 -0
- tokenizer_config.json +21 -0
- train_results.json +8 -0
- trainer_state.json +337 -0
- training_args.bin +3 -0
.gitattributes
CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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all_results.json
ADDED
@@ -0,0 +1,20 @@
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{
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"epoch": 2.0,
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"eval_accuracy": 0.3333333333333333,
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"eval_loss": 1.0986275672912598,
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"eval_runtime": 4.8281,
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"eval_samples": 2490,
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"eval_samples_per_second": 515.736,
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"eval_steps_per_second": 64.622,
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"predict_accuracy": 0.3333333333333333,
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"predict_loss": 1.0986275672912598,
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"predict_runtime": 9.6687,
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"predict_samples": 5010,
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"predict_samples_per_second": 518.166,
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"predict_steps_per_second": 64.848,
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"train_loss": 1.0999860929852203,
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"train_runtime": 4899.674,
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"train_samples": 392702,
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"train_samples_per_second": 160.297,
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"train_steps_per_second": 5.009
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}
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config.json
ADDED
@@ -0,0 +1,41 @@
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{
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"_name_or_path": "cardiffnlp/twitter-xlm-roberta-base",
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"architectures": [
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"XLMRobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"finetuning_task": "xnli",
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "xlm-roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_past": true,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.25.1",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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eval_results.json
ADDED
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{
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"epoch": 2.0,
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"eval_accuracy": 0.3333333333333333,
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"eval_loss": 1.0986275672912598,
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"eval_runtime": 4.8281,
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"eval_samples": 2490,
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"eval_samples_per_second": 515.736,
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"eval_steps_per_second": 64.622
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}
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predict_results.json
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{
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"predict_accuracy": 0.3333333333333333,
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"predict_loss": 1.0986275672912598,
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"predict_runtime": 9.6687,
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"predict_samples": 5010,
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"predict_samples_per_second": 518.166,
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"predict_steps_per_second": 64.848
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}
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predictions.txt
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1700 entailment
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1701 entailment
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1702 entailment
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1728 entailment
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1744 entailment
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1745 entailment
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1746 entailment
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1748 entailment
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1749 entailment
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1750 entailment
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1751 entailment
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1752 entailment
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1754 entailment
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1755 entailment
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1756 entailment
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1758 entailment
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1759 entailment
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1762 |
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1760 entailment
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1763 |
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1761 entailment
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1764 |
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1762 entailment
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1765 |
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1763 entailment
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1766 |
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1764 entailment
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1767 |
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1765 entailment
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1768 |
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1766 entailment
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1769 |
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1767 entailment
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1768 entailment
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1771 |
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1769 entailment
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1770 entailment
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1773 |
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1771 entailment
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1772 entailment
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1773 entailment
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1775 entailment
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1776 entailment
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1800 |
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1798 entailment
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1800 entailment
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1801 entailment
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1822 entailment
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1824 entailment
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1827 |
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1828 |
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1829 |
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1830 |
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1828 entailment
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1831 |
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1832 |
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1830 entailment
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1834 |
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1832 entailment
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1835 |
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1833 entailment
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1834 entailment
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1837 |
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1835 entailment
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1838 |
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1836 entailment
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1838 entailment
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1839 entailment
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1840 entailment
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1854 entailment
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1855 entailment
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1856 entailment
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1857 entailment
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1858 entailment
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1859 entailment
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1860 entailment
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1861 entailment
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1864 |
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1862 entailment
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1863 entailment
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1864 entailment
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1867 |
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1865 entailment
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1866 entailment
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1870 entailment
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1871 entailment
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1873 entailment
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1875 entailment
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1876 entailment
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1877 entailment
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1878 entailment
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1879 entailment
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1880 entailment
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1881 entailment
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1882 entailment
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1883 entailment
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1884 entailment
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1885 entailment
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1886 entailment
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1888 entailment
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1889 entailment
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1890 entailment
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1891 entailment
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1892 entailment
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1894 entailment
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1895 entailment
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1896 entailment
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1897 entailment
|
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1898 entailment
|
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1899 entailment
|
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1900 entailment
|
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1901 entailment
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1902 entailment
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1903 entailment
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1906 |
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1904 entailment
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1907 |
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1905 entailment
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1908 |
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1906 entailment
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1907 entailment
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1908 entailment
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1909 entailment
|
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1910 entailment
|
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1911 entailment
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1912 entailment
|
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1913 entailment
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1914 entailment
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1915 entailment
|
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1916 entailment
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|
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1918 entailment
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1919 entailment
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1920 entailment
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1921 entailment
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1922 entailment
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1923 entailment
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1924 entailment
|
1927 |
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1925 entailment
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1928 |
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1926 entailment
|
1929 |
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1927 entailment
|
1930 |
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1928 entailment
|
1931 |
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1929 entailment
|
1932 |
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1930 entailment
|
1933 |
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1931 entailment
|
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1932 entailment
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1933 entailment
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1934 entailment
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1935 entailment
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1936 entailment
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1937 entailment
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1938 entailment
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1939 entailment
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1940 entailment
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1941 entailment
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1942 entailment
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1943 entailment
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1944 entailment
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1945 entailment
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1946 entailment
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1947 entailment
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1948 entailment
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1949 entailment
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1950 entailment
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1951 entailment
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1952 entailment
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1954 entailment
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1961 entailment
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1962 entailment
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1963 entailment
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1968 entailment
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1969 entailment
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1970 entailment
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1971 entailment
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1972 entailment
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1973 entailment
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1974 entailment
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1975 entailment
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1976 entailment
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1977 entailment
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1978 entailment
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1979 entailment
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1980 entailment
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1981 entailment
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1982 entailment
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1983 entailment
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1984 entailment
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2000 entailment
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2001 entailment
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2002 entailment
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2003 entailment
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2006 entailment
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2007 entailment
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2008 entailment
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2009 entailment
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2012 |
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2010 entailment
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2011 entailment
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2012 entailment
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2013 entailment
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2014 entailment
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2015 entailment
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2016 entailment
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2017 entailment
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2021 entailment
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2022 entailment
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2024 entailment
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2025 entailment
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2026 entailment
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2027 entailment
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2028 entailment
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2029 entailment
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2030 entailment
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2031 entailment
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2032 entailment
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2033 entailment
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2035 entailment
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2036 entailment
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2037 entailment
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