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distilbert-base-uncased__subj__train-8-8

Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
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+ ---
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+ license: apache-2.0
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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: distilbert-base-uncased__subj__train-8-8
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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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+ # distilbert-base-uncased__subj__train-8-8
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3160
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+ - Accuracy: 0.8735
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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: 2e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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: 50
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+ - mixed_precision_training: Native AMP
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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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+ | 0.7187 | 1.0 | 3 | 0.6776 | 1.0 |
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+ | 0.684 | 2.0 | 6 | 0.6608 | 1.0 |
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+ | 0.6532 | 3.0 | 9 | 0.6364 | 1.0 |
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+ | 0.5996 | 4.0 | 12 | 0.6119 | 1.0 |
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+ | 0.5242 | 5.0 | 15 | 0.5806 | 1.0 |
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+ | 0.4612 | 6.0 | 18 | 0.5320 | 1.0 |
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+ | 0.4192 | 7.0 | 21 | 0.4714 | 1.0 |
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+ | 0.3274 | 8.0 | 24 | 0.4071 | 1.0 |
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+ | 0.2871 | 9.0 | 27 | 0.3378 | 1.0 |
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+ | 0.2082 | 10.0 | 30 | 0.2822 | 1.0 |
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+ | 0.1692 | 11.0 | 33 | 0.2271 | 1.0 |
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+ | 0.1242 | 12.0 | 36 | 0.1793 | 1.0 |
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+ | 0.0977 | 13.0 | 39 | 0.1417 | 1.0 |
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+ | 0.0776 | 14.0 | 42 | 0.1117 | 1.0 |
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+ | 0.0631 | 15.0 | 45 | 0.0894 | 1.0 |
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+ | 0.0453 | 16.0 | 48 | 0.0733 | 1.0 |
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+ | 0.0399 | 17.0 | 51 | 0.0617 | 1.0 |
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+ | 0.0333 | 18.0 | 54 | 0.0528 | 1.0 |
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+ | 0.0266 | 19.0 | 57 | 0.0454 | 1.0 |
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+ | 0.0234 | 20.0 | 60 | 0.0393 | 1.0 |
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+ | 0.0223 | 21.0 | 63 | 0.0345 | 1.0 |
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+ | 0.0195 | 22.0 | 66 | 0.0309 | 1.0 |
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+ | 0.0161 | 23.0 | 69 | 0.0281 | 1.0 |
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+ | 0.0167 | 24.0 | 72 | 0.0260 | 1.0 |
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+ | 0.0163 | 25.0 | 75 | 0.0242 | 1.0 |
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+ | 0.0134 | 26.0 | 78 | 0.0227 | 1.0 |
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+ | 0.0128 | 27.0 | 81 | 0.0214 | 1.0 |
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+ | 0.0101 | 28.0 | 84 | 0.0204 | 1.0 |
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+ | 0.0109 | 29.0 | 87 | 0.0194 | 1.0 |
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+ | 0.0112 | 30.0 | 90 | 0.0186 | 1.0 |
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+ | 0.0108 | 31.0 | 93 | 0.0179 | 1.0 |
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+ | 0.011 | 32.0 | 96 | 0.0174 | 1.0 |
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+ | 0.0099 | 33.0 | 99 | 0.0169 | 1.0 |
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+ | 0.0083 | 34.0 | 102 | 0.0164 | 1.0 |
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+ | 0.0096 | 35.0 | 105 | 0.0160 | 1.0 |
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+ | 0.01 | 36.0 | 108 | 0.0156 | 1.0 |
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+ | 0.0084 | 37.0 | 111 | 0.0152 | 1.0 |
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+ | 0.0089 | 38.0 | 114 | 0.0149 | 1.0 |
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+ | 0.0073 | 39.0 | 117 | 0.0146 | 1.0 |
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+ | 0.0082 | 40.0 | 120 | 0.0143 | 1.0 |
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+ | 0.008 | 41.0 | 123 | 0.0141 | 1.0 |
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+ | 0.0093 | 42.0 | 126 | 0.0139 | 1.0 |
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+ | 0.0078 | 43.0 | 129 | 0.0138 | 1.0 |
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+ | 0.0086 | 44.0 | 132 | 0.0136 | 1.0 |
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+ | 0.009 | 45.0 | 135 | 0.0135 | 1.0 |
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+ | 0.0072 | 46.0 | 138 | 0.0134 | 1.0 |
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+ | 0.0075 | 47.0 | 141 | 0.0133 | 1.0 |
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+ | 0.0082 | 48.0 | 144 | 0.0133 | 1.0 |
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+ | 0.0068 | 49.0 | 147 | 0.0132 | 1.0 |
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+ | 0.0074 | 50.0 | 150 | 0.0132 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.15.0
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+ - Pytorch 1.10.2+cu102
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+ - Datasets 1.18.2
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+ - Tokenizers 0.10.3