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simonycl
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best_model-sst-2-32-13

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ base_model: bert-base-uncased
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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: best_model-sst-2-32-13
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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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+ # best_model-sst-2-32-13
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0073
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+ - Accuracy: 0.6875
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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: 1e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 150
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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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+ | No log | 1.0 | 2 | 0.6566 | 0.6719 |
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+ | No log | 2.0 | 4 | 0.6561 | 0.6719 |
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+ | No log | 3.0 | 6 | 0.6553 | 0.6719 |
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+ | No log | 4.0 | 8 | 0.6542 | 0.6719 |
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+ | 0.4607 | 5.0 | 10 | 0.6525 | 0.6719 |
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+ | 0.4607 | 6.0 | 12 | 0.6504 | 0.6719 |
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+ | 0.4607 | 7.0 | 14 | 0.6480 | 0.6719 |
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+ | 0.4607 | 8.0 | 16 | 0.6454 | 0.6719 |
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+ | 0.4607 | 9.0 | 18 | 0.6432 | 0.6719 |
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+ | 0.4685 | 10.0 | 20 | 0.6408 | 0.6719 |
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+ | 0.4685 | 11.0 | 22 | 0.6383 | 0.6562 |
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+ | 0.4685 | 12.0 | 24 | 0.6357 | 0.6719 |
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+ | 0.4685 | 13.0 | 26 | 0.6331 | 0.6562 |
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+ | 0.4685 | 14.0 | 28 | 0.6310 | 0.6719 |
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+ | 0.444 | 15.0 | 30 | 0.6289 | 0.6719 |
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+ | 0.444 | 16.0 | 32 | 0.6270 | 0.6562 |
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+ | 0.444 | 17.0 | 34 | 0.6253 | 0.6562 |
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+ | 0.444 | 18.0 | 36 | 0.6235 | 0.6406 |
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+ | 0.444 | 19.0 | 38 | 0.6216 | 0.6406 |
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+ | 0.4147 | 20.0 | 40 | 0.6199 | 0.6406 |
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+ | 0.4147 | 21.0 | 42 | 0.6183 | 0.6562 |
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+ | 0.4147 | 22.0 | 44 | 0.6168 | 0.6562 |
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+ | 0.4147 | 23.0 | 46 | 0.6155 | 0.6562 |
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+ | 0.4147 | 24.0 | 48 | 0.6144 | 0.6562 |
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+ | 0.409 | 25.0 | 50 | 0.6133 | 0.6406 |
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+ | 0.409 | 26.0 | 52 | 0.6123 | 0.6406 |
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+ | 0.409 | 27.0 | 54 | 0.6116 | 0.6562 |
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+ | 0.409 | 28.0 | 56 | 0.6110 | 0.6562 |
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+ | 0.409 | 29.0 | 58 | 0.6103 | 0.6562 |
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+ | 0.3614 | 30.0 | 60 | 0.6099 | 0.6719 |
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+ | 0.3614 | 31.0 | 62 | 0.6094 | 0.6719 |
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+ | 0.3614 | 32.0 | 64 | 0.6090 | 0.6719 |
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+ | 0.3614 | 33.0 | 66 | 0.6090 | 0.6719 |
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+ | 0.3614 | 34.0 | 68 | 0.6090 | 0.6875 |
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+ | 0.3297 | 35.0 | 70 | 0.6093 | 0.6875 |
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+ | 0.3297 | 36.0 | 72 | 0.6095 | 0.6875 |
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+ | 0.3297 | 37.0 | 74 | 0.6093 | 0.6875 |
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+ | 0.3297 | 38.0 | 76 | 0.6089 | 0.6875 |
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+ | 0.3297 | 39.0 | 78 | 0.6081 | 0.6875 |
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+ | 0.2957 | 40.0 | 80 | 0.6072 | 0.6875 |
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+ | 0.2957 | 41.0 | 82 | 0.6064 | 0.7031 |
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+ | 0.2957 | 42.0 | 84 | 0.6054 | 0.6875 |
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+ | 0.2957 | 43.0 | 86 | 0.6041 | 0.6719 |
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+ | 0.2957 | 44.0 | 88 | 0.6031 | 0.6719 |
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+ | 0.2704 | 45.0 | 90 | 0.6022 | 0.6875 |
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+ | 0.2704 | 46.0 | 92 | 0.6017 | 0.6875 |
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+ | 0.2704 | 47.0 | 94 | 0.6012 | 0.6875 |
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+ | 0.2704 | 48.0 | 96 | 0.6008 | 0.6719 |
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+ | 0.2704 | 49.0 | 98 | 0.5998 | 0.6719 |
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+ | 0.2302 | 50.0 | 100 | 0.5987 | 0.6875 |
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+ | 0.2302 | 51.0 | 102 | 0.5977 | 0.6875 |
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+ | 0.2302 | 52.0 | 104 | 0.5959 | 0.6875 |
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+ | 0.2302 | 53.0 | 106 | 0.5935 | 0.6719 |
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+ | 0.2302 | 54.0 | 108 | 0.5913 | 0.6719 |
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+ | 0.198 | 55.0 | 110 | 0.5895 | 0.6719 |
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+ | 0.198 | 56.0 | 112 | 0.5882 | 0.6719 |
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+ | 0.198 | 57.0 | 114 | 0.5865 | 0.6875 |
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+ | 0.198 | 58.0 | 116 | 0.5854 | 0.7031 |
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+ | 0.198 | 59.0 | 118 | 0.5852 | 0.7031 |
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+ | 0.1729 | 60.0 | 120 | 0.5854 | 0.7031 |
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+ | 0.1729 | 61.0 | 122 | 0.5857 | 0.7031 |
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+ | 0.1729 | 62.0 | 124 | 0.5861 | 0.6875 |
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+ | 0.1729 | 63.0 | 126 | 0.5864 | 0.6875 |
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+ | 0.1729 | 64.0 | 128 | 0.5866 | 0.6875 |
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+ | 0.1495 | 65.0 | 130 | 0.5863 | 0.6719 |
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+ | 0.1495 | 66.0 | 132 | 0.5858 | 0.6719 |
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+ | 0.1495 | 67.0 | 134 | 0.5856 | 0.6875 |
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+ | 0.1495 | 68.0 | 136 | 0.5860 | 0.6875 |
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+ | 0.1495 | 69.0 | 138 | 0.5860 | 0.6719 |
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+ | 0.1223 | 70.0 | 140 | 0.5863 | 0.6719 |
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+ | 0.1223 | 71.0 | 142 | 0.5870 | 0.6875 |
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+ | 0.1223 | 72.0 | 144 | 0.5881 | 0.6875 |
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+ | 0.1223 | 73.0 | 146 | 0.5890 | 0.6719 |
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+ | 0.1223 | 74.0 | 148 | 0.5899 | 0.6719 |
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+ | 0.1034 | 75.0 | 150 | 0.5909 | 0.6719 |
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+ | 0.1034 | 76.0 | 152 | 0.5920 | 0.6719 |
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+ | 0.1034 | 77.0 | 154 | 0.5935 | 0.6562 |
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+ | 0.1034 | 78.0 | 156 | 0.5953 | 0.6562 |
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+ | 0.1034 | 79.0 | 158 | 0.5969 | 0.6562 |
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+ | 0.087 | 80.0 | 160 | 0.5984 | 0.6562 |
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+ | 0.087 | 81.0 | 162 | 0.6008 | 0.6562 |
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+ | 0.087 | 82.0 | 164 | 0.6031 | 0.6719 |
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+ | 0.087 | 83.0 | 166 | 0.6057 | 0.6562 |
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+ | 0.087 | 84.0 | 168 | 0.6088 | 0.6562 |
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+ | 0.0705 | 85.0 | 170 | 0.6126 | 0.6562 |
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+ | 0.0705 | 86.0 | 172 | 0.6164 | 0.6562 |
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+ | 0.0705 | 87.0 | 174 | 0.6198 | 0.6719 |
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+ | 0.0705 | 88.0 | 176 | 0.6227 | 0.6719 |
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+ | 0.0705 | 89.0 | 178 | 0.6257 | 0.6719 |
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+ | 0.0551 | 90.0 | 180 | 0.6288 | 0.6719 |
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+ | 0.0551 | 91.0 | 182 | 0.6321 | 0.6719 |
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+ | 0.0551 | 92.0 | 184 | 0.6360 | 0.6719 |
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+ | 0.0551 | 93.0 | 186 | 0.6403 | 0.6875 |
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+ | 0.0551 | 94.0 | 188 | 0.6443 | 0.6875 |
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+ | 0.0447 | 95.0 | 190 | 0.6489 | 0.6875 |
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+ | 0.0447 | 96.0 | 192 | 0.6534 | 0.6875 |
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+ | 0.0447 | 97.0 | 194 | 0.6609 | 0.7031 |
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+ | 0.0447 | 98.0 | 196 | 0.6689 | 0.7031 |
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+ | 0.0447 | 99.0 | 198 | 0.6772 | 0.7188 |
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+ | 0.0345 | 100.0 | 200 | 0.6875 | 0.7188 |
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+ | 0.0345 | 101.0 | 202 | 0.6968 | 0.7188 |
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+ | 0.0345 | 102.0 | 204 | 0.7052 | 0.7188 |
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+ | 0.0345 | 103.0 | 206 | 0.7126 | 0.7188 |
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+ | 0.0345 | 104.0 | 208 | 0.7181 | 0.7188 |
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+ | 0.0274 | 105.0 | 210 | 0.7234 | 0.7188 |
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+ | 0.0274 | 106.0 | 212 | 0.7282 | 0.7188 |
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+ | 0.0274 | 107.0 | 214 | 0.7361 | 0.7188 |
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+ | 0.0274 | 108.0 | 216 | 0.7440 | 0.7031 |
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+ | 0.0274 | 109.0 | 218 | 0.7539 | 0.7031 |
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+ | 0.0218 | 110.0 | 220 | 0.7658 | 0.7031 |
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+ | 0.0218 | 111.0 | 222 | 0.7772 | 0.7031 |
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+ | 0.0218 | 112.0 | 224 | 0.7882 | 0.7031 |
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+ | 0.0218 | 113.0 | 226 | 0.7977 | 0.7031 |
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+ | 0.0218 | 114.0 | 228 | 0.8047 | 0.7031 |
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+ | 0.0168 | 115.0 | 230 | 0.8103 | 0.7031 |
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+ | 0.0168 | 116.0 | 232 | 0.8135 | 0.7031 |
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+ | 0.0168 | 117.0 | 234 | 0.8157 | 0.7031 |
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+ | 0.0168 | 118.0 | 236 | 0.8186 | 0.7031 |
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+ | 0.0168 | 119.0 | 238 | 0.8213 | 0.7031 |
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+ | 0.0138 | 120.0 | 240 | 0.8240 | 0.6875 |
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+ | 0.0138 | 121.0 | 242 | 0.8262 | 0.6875 |
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+ | 0.0138 | 122.0 | 244 | 0.8296 | 0.6875 |
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+ | 0.0138 | 123.0 | 246 | 0.8339 | 0.6875 |
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+ | 0.0138 | 124.0 | 248 | 0.8392 | 0.6875 |
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+ | 0.0115 | 125.0 | 250 | 0.8451 | 0.6875 |
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+ | 0.0115 | 126.0 | 252 | 0.8508 | 0.6875 |
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+ | 0.0115 | 127.0 | 254 | 0.8574 | 0.6875 |
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+ | 0.0115 | 128.0 | 256 | 0.8640 | 0.6875 |
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+ | 0.0115 | 129.0 | 258 | 0.8707 | 0.6875 |
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+ | 0.0096 | 130.0 | 260 | 0.8776 | 0.6875 |
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+ | 0.0096 | 131.0 | 262 | 0.8845 | 0.6875 |
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+ | 0.0096 | 132.0 | 264 | 0.8938 | 0.6875 |
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+ | 0.0096 | 133.0 | 266 | 0.9021 | 0.6875 |
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+ | 0.0096 | 134.0 | 268 | 0.9102 | 0.6875 |
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+ | 0.0083 | 135.0 | 270 | 0.9181 | 0.6875 |
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+ | 0.0083 | 136.0 | 272 | 0.9260 | 0.6875 |
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+ | 0.0083 | 137.0 | 274 | 0.9338 | 0.6875 |
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+ | 0.0083 | 138.0 | 276 | 0.9416 | 0.6875 |
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+ | 0.0083 | 139.0 | 278 | 0.9488 | 0.6875 |
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+ | 0.0071 | 140.0 | 280 | 0.9566 | 0.6875 |
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+ | 0.0071 | 141.0 | 282 | 0.9635 | 0.6875 |
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+ | 0.0071 | 142.0 | 284 | 0.9707 | 0.6875 |
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+ | 0.0071 | 143.0 | 286 | 0.9769 | 0.6875 |
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+ | 0.0071 | 144.0 | 288 | 0.9825 | 0.6875 |
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+ | 0.0061 | 145.0 | 290 | 0.9878 | 0.6875 |
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+ | 0.0061 | 146.0 | 292 | 0.9926 | 0.6875 |
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+ | 0.0061 | 147.0 | 294 | 0.9962 | 0.6875 |
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+ | 0.0061 | 148.0 | 296 | 1.0002 | 0.6875 |
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+ | 0.0061 | 149.0 | 298 | 1.0036 | 0.6875 |
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+ | 0.0054 | 150.0 | 300 | 1.0073 | 0.6875 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.0.dev0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.4.0
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+ - Tokenizers 0.13.3