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roberta-Reflections-goodareas-sweeps-current

Text Classification
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roberta
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text-embeddings-inference
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README.md CHANGED
@@ -19,13 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # roberta-Reflections-goodareas-sweeps-current
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- This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2951
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- - Accuracy: 0.8386
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- - Precision: 0.3101
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- - Recall: 0.4819
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- - F1: 0.3774
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  ## Model description
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@@ -44,39 +44,38 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3.798952171015902e-06
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  - train_batch_size: 32
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  - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - lr_scheduler_warmup_ratio: 0.1
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  - num_epochs: 20
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.4514 | 1.0 | 76 | 0.2316 | 0.8936 | 0.0 | 0.0 | 0.0 |
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- | 0.3364 | 2.0 | 152 | 0.1945 | 0.8985 | 0.0 | 0.0 | 0.0 |
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- | 0.2646 | 3.0 | 228 | 0.1475 | 0.9010 | 1.0 | 0.0241 | 0.0471 |
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- | 0.2532 | 4.0 | 304 | 0.1316 | 0.8985 | 0.0 | 0.0 | 0.0 |
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- | 0.25 | 5.0 | 380 | 0.2167 | 0.8655 | 0.3953 | 0.6145 | 0.4811 |
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- | 0.2406 | 6.0 | 456 | 0.1215 | 0.8961 | 0.4167 | 0.0602 | 0.1053 |
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- | 0.2411 | 7.0 | 532 | 0.2102 | 0.8692 | 0.3966 | 0.5542 | 0.4623 |
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- | 0.2166 | 8.0 | 608 | 0.1978 | 0.8692 | 0.3846 | 0.4819 | 0.4278 |
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- | 0.2043 | 9.0 | 684 | 0.1570 | 0.8912 | 0.45 | 0.3253 | 0.3776 |
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- | 0.1978 | 10.0 | 760 | 0.1350 | 0.8973 | 0.4815 | 0.1566 | 0.2364 |
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- | 0.1835 | 11.0 | 836 | 0.1786 | 0.8839 | 0.4167 | 0.3614 | 0.3871 |
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- | 0.1681 | 12.0 | 912 | 0.1614 | 0.8888 | 0.4259 | 0.2771 | 0.3358 |
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- | 0.1744 | 13.0 | 988 | 0.1784 | 0.8790 | 0.3710 | 0.2771 | 0.3172 |
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- | 0.1494 | 14.0 | 1064 | 0.2846 | 0.8362 | 0.3265 | 0.5783 | 0.4174 |
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- | 0.1396 | 15.0 | 1140 | 0.2666 | 0.8496 | 0.3438 | 0.5301 | 0.4171 |
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- | 0.1284 | 16.0 | 1216 | 0.3044 | 0.8362 | 0.3191 | 0.5422 | 0.4018 |
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- | 0.1339 | 17.0 | 1292 | 0.2202 | 0.8667 | 0.3556 | 0.3855 | 0.3699 |
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- | 0.1086 | 18.0 | 1368 | 0.2773 | 0.8472 | 0.325 | 0.4699 | 0.3842 |
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- | 0.1155 | 19.0 | 1444 | 0.2841 | 0.8435 | 0.3171 | 0.4699 | 0.3786 |
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- | 0.1075 | 20.0 | 1520 | 0.2951 | 0.8386 | 0.3101 | 0.4819 | 0.3774 |
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  ### Framework versions
 
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  # roberta-Reflections-goodareas-sweeps-current
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+ This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1937
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+ - Accuracy: 0.8562
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+ - Precision: 0.3984
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+ - Recall: 0.5632
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+ - F1: 0.4667
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3.693911058164899e-06
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  - train_batch_size: 32
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  - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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  - num_epochs: 20
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.3925 | 1.0 | 52 | 0.1759 | 0.8883 | 0.0 | 0.0 | 0.0 |
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+ | 0.3241 | 2.0 | 104 | 0.1606 | 0.8883 | 0.0 | 0.0 | 0.0 |
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+ | 0.2914 | 3.0 | 156 | 0.1744 | 0.8883 | 0.0 | 0.0 | 0.0 |
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+ | 0.2821 | 4.0 | 208 | 0.2609 | 0.8909 | 0.75 | 0.0345 | 0.0659 |
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+ | 0.2739 | 5.0 | 260 | 0.1763 | 0.8935 | 0.75 | 0.0690 | 0.1263 |
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+ | 0.2533 | 6.0 | 312 | 0.1390 | 0.8922 | 0.6154 | 0.0920 | 0.16 |
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+ | 0.2482 | 7.0 | 364 | 0.2199 | 0.8755 | 0.4490 | 0.5057 | 0.4757 |
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+ | 0.2362 | 8.0 | 416 | 0.2124 | 0.8652 | 0.4286 | 0.6207 | 0.5070 |
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+ | 0.2375 | 9.0 | 468 | 0.1351 | 0.8973 | 0.5614 | 0.3678 | 0.4444 |
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+ | 0.228 | 10.0 | 520 | 0.1650 | 0.8870 | 0.4945 | 0.5172 | 0.5056 |
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+ | 0.2212 | 11.0 | 572 | 0.1771 | 0.8845 | 0.4851 | 0.5632 | 0.5213 |
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+ | 0.2217 | 12.0 | 624 | 0.1756 | 0.8832 | 0.4792 | 0.5287 | 0.5027 |
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+ | 0.2109 | 13.0 | 676 | 0.1942 | 0.8614 | 0.4118 | 0.5632 | 0.4757 |
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+ | 0.2018 | 14.0 | 728 | 0.1795 | 0.8678 | 0.4298 | 0.5632 | 0.4876 |
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+ | 0.2013 | 15.0 | 780 | 0.1817 | 0.8652 | 0.4211 | 0.5517 | 0.4776 |
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+ | 0.1943 | 16.0 | 832 | 0.2071 | 0.8575 | 0.4077 | 0.6092 | 0.4885 |
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+ | 0.2023 | 17.0 | 884 | 0.2143 | 0.8498 | 0.3897 | 0.6092 | 0.4753 |
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+ | 0.1924 | 18.0 | 936 | 0.1966 | 0.8562 | 0.4031 | 0.5977 | 0.4815 |
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+ | 0.183 | 19.0 | 988 | 0.1914 | 0.8614 | 0.4118 | 0.5632 | 0.4757 |
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+ | 0.191 | 20.0 | 1040 | 0.1937 | 0.8562 | 0.3984 | 0.5632 | 0.4667 |
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  ### Framework versions
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