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jhonalevc1995
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test_roberta-base-uncased_fine

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: FacebookAI/roberta-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: test_roberta-base-uncased_fine
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+ results: []
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+ ---
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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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+
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+ # test_roberta-base-uncased_fine
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+
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+ This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7702
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+ - Accuracy: 0.5
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.4
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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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: 200
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 10.6938 | 2.0 | 2 | 252.3604 | 0.25 |
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+ | 298.9333 | 4.0 | 4 | 442.8570 | 0.25 |
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+ | 211.2317 | 6.0 | 6 | 111.0638 | 0.25 |
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+ | 106.4107 | 8.0 | 8 | 84.1177 | 0.75 |
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+ | 158.3927 | 10.0 | 10 | 51.9647 | 0.75 |
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+ | 6.2279 | 12.0 | 12 | 173.9537 | 0.25 |
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+ | 182.2623 | 14.0 | 14 | 273.0900 | 0.25 |
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+ | 144.4092 | 16.0 | 16 | 118.2153 | 0.25 |
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+ | 16.2253 | 18.0 | 18 | 29.9255 | 0.75 |
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+ | 61.4584 | 20.0 | 20 | 15.3424 | 0.75 |
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+ | 25.5289 | 22.0 | 22 | 73.0185 | 0.25 |
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+ | 33.1599 | 24.0 | 24 | 5.7046 | 0.75 |
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+ | 16.6906 | 26.0 | 26 | 6.8680 | 0.25 |
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+ | 3.3119 | 28.0 | 28 | 25.7839 | 0.25 |
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+ | 5.7235 | 30.0 | 30 | 15.8690 | 0.75 |
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+ | 34.8772 | 32.0 | 32 | 5.4515 | 0.75 |
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+ | 37.1887 | 34.0 | 34 | 77.3684 | 0.25 |
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+ | 37.5714 | 36.0 | 36 | 1.4211 | 0.75 |
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+ | 14.3135 | 38.0 | 38 | 7.8595 | 0.25 |
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+ | 5.5931 | 40.0 | 40 | 16.6094 | 0.25 |
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+ | 1.8101 | 42.0 | 42 | 18.0400 | 0.25 |
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+ | 4.0269 | 44.0 | 44 | 14.3646 | 0.25 |
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+ | 5.9638 | 46.0 | 46 | 11.1460 | 0.25 |
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+ | 8.1137 | 48.0 | 48 | 8.4826 | 0.25 |
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+ | 8.3957 | 50.0 | 50 | 6.5438 | 0.25 |
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+ | 8.5907 | 52.0 | 52 | 5.2709 | 0.25 |
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+ | 4.1322 | 54.0 | 54 | 16.3942 | 0.25 |
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+ | 4.1029 | 56.0 | 56 | 13.8090 | 0.75 |
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+ | 28.9367 | 58.0 | 58 | 5.2299 | 0.75 |
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+ | 28.4754 | 60.0 | 60 | 62.0075 | 0.25 |
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+ | 30.8988 | 62.0 | 62 | 0.7625 | 0.75 |
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+ | 8.1166 | 64.0 | 64 | 12.6710 | 0.25 |
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+ | 3.2467 | 66.0 | 66 | 2.3880 | 0.75 |
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+ | 10.7889 | 68.0 | 68 | 5.7275 | 0.25 |
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+ | 22.3353 | 70.0 | 70 | 12.9041 | 0.75 |
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+ | 8.1383 | 72.0 | 72 | 41.1468 | 0.25 |
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+ | 36.7992 | 74.0 | 74 | 42.5415 | 0.25 |
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+ | 2.0152 | 76.0 | 76 | 20.8100 | 0.75 |
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+ | 60.7814 | 78.0 | 78 | 27.4327 | 0.75 |
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+ | 34.0779 | 80.0 | 80 | 9.5079 | 0.25 |
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+ | 21.0197 | 82.0 | 82 | 24.1783 | 0.25 |
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+ | 7.6894 | 84.0 | 84 | 3.8363 | 0.75 |
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+ | 7.4756 | 86.0 | 86 | 8.7418 | 0.25 |
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+ | 14.3838 | 88.0 | 88 | 7.2120 | 0.75 |
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+ | 3.0887 | 90.0 | 90 | 1.2209 | 0.25 |
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+ | 1.8247 | 92.0 | 92 | 6.9209 | 0.75 |
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+ | 12.0203 | 94.0 | 94 | 12.7842 | 0.25 |
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+ | 8.0623 | 96.0 | 96 | 3.4052 | 0.75 |
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+ | 2.7705 | 98.0 | 98 | 20.0414 | 0.25 |
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+ | 15.1917 | 100.0 | 100 | 1.2432 | 0.75 |
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+ | 1.2199 | 102.0 | 102 | 1.3510 | 0.25 |
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+ | 10.4742 | 104.0 | 104 | 1.7442 | 0.75 |
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+ | 17.1792 | 106.0 | 106 | 29.1314 | 0.25 |
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+ | 6.9967 | 108.0 | 108 | 8.8842 | 0.75 |
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+ | 27.7392 | 110.0 | 110 | 8.9014 | 0.75 |
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+ | 1.9595 | 112.0 | 112 | 10.4839 | 0.25 |
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+ | 2.4346 | 114.0 | 114 | 2.5657 | 0.25 |
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+ | 9.1093 | 116.0 | 116 | 0.9068 | 0.75 |
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+ | 15.7093 | 118.0 | 118 | 25.8976 | 0.25 |
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+ | 5.3074 | 120.0 | 120 | 7.7724 | 0.75 |
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+ | 21.9532 | 122.0 | 122 | 8.1528 | 0.75 |
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+ | 0.9267 | 124.0 | 124 | 26.0336 | 0.25 |
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+ | 21.7107 | 126.0 | 126 | 14.6756 | 0.25 |
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+ | 9.9152 | 128.0 | 128 | 8.1630 | 0.75 |
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+ | 9.7847 | 130.0 | 130 | 7.8175 | 0.25 |
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+ | 6.7746 | 132.0 | 132 | 1.0481 | 0.25 |
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+ | 14.4615 | 134.0 | 134 | 8.8793 | 0.75 |
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+ | 11.8844 | 136.0 | 136 | 9.5880 | 0.25 |
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+ | 12.1117 | 138.0 | 138 | 8.3064 | 0.25 |
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+ | 8.4027 | 140.0 | 140 | 6.0652 | 0.75 |
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+ | 5.8957 | 142.0 | 142 | 13.8286 | 0.25 |
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+ | 10.5928 | 144.0 | 144 | 11.3976 | 0.25 |
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+ | 5.7989 | 146.0 | 146 | 4.3992 | 0.75 |
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+ | 3.2276 | 148.0 | 148 | 14.5699 | 0.25 |
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+ | 13.8288 | 150.0 | 150 | 12.2211 | 0.25 |
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+ | 2.9975 | 152.0 | 152 | 3.4190 | 0.75 |
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+ | 2.5391 | 154.0 | 154 | 13.8731 | 0.25 |
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+ | 11.4397 | 156.0 | 156 | 11.4427 | 0.25 |
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+ | 4.3493 | 158.0 | 158 | 2.8519 | 0.75 |
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+ | 1.8169 | 160.0 | 160 | 4.8652 | 0.25 |
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+ | 3.0403 | 162.0 | 162 | 3.1370 | 0.75 |
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+ | 5.9224 | 164.0 | 164 | 1.0573 | 0.75 |
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+ | 7.1067 | 166.0 | 166 | 14.0748 | 0.25 |
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+ | 6.5255 | 168.0 | 168 | 0.7829 | 0.75 |
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+ | 5.3116 | 170.0 | 170 | 2.0900 | 0.75 |
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+ | 1.927 | 172.0 | 172 | 3.1757 | 0.25 |
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+ | 1.8274 | 174.0 | 174 | 0.5881 | 0.75 |
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+ | 5.5108 | 176.0 | 176 | 6.2222 | 0.25 |
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+ | 1.3478 | 178.0 | 178 | 1.1449 | 0.75 |
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+ | 2.7849 | 180.0 | 180 | 3.2430 | 0.25 |
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+ | 1.8472 | 182.0 | 182 | 0.5665 | 0.75 |
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+ | 1.8895 | 184.0 | 184 | 1.9489 | 0.25 |
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+ | 2.4857 | 186.0 | 186 | 0.6363 | 0.75 |
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+ | 2.2369 | 188.0 | 188 | 1.2758 | 0.25 |
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+ | 1.5309 | 190.0 | 190 | 0.5841 | 0.75 |
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+ | 1.7197 | 192.0 | 192 | 0.5974 | 0.75 |
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+ | 1.928 | 194.0 | 194 | 0.7480 | 0.25 |
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+ | 2.7589 | 196.0 | 196 | 2.8053 | 0.25 |
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+ | 1.4242 | 198.0 | 198 | 1.3693 | 0.25 |
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+ | 2.1382 | 200.0 | 200 | 0.5714 | 0.75 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.1
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+ - Tokenizers 0.19.1