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distilbert-base-uncased__subj__train-8-6

Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Inference Endpoints
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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-8-6
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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-8-6
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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: 0.6075
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+ - Accuracy: 0.7485
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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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+ | 0.7163 | 1.0 | 3 | 0.6923 | 0.5 |
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+ | 0.6648 | 2.0 | 6 | 0.6838 | 0.5 |
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+ | 0.6329 | 3.0 | 9 | 0.6747 | 0.75 |
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+ | 0.5836 | 4.0 | 12 | 0.6693 | 0.5 |
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+ | 0.5287 | 5.0 | 15 | 0.6670 | 0.25 |
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+ | 0.4585 | 6.0 | 18 | 0.6517 | 0.5 |
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+ | 0.415 | 7.0 | 21 | 0.6290 | 0.5 |
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+ | 0.3353 | 8.0 | 24 | 0.6019 | 0.5 |
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+ | 0.2841 | 9.0 | 27 | 0.5613 | 0.75 |
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+ | 0.2203 | 10.0 | 30 | 0.5222 | 1.0 |
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+ | 0.1743 | 11.0 | 33 | 0.4769 | 1.0 |
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+ | 0.1444 | 12.0 | 36 | 0.4597 | 1.0 |
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+ | 0.1079 | 13.0 | 39 | 0.4462 | 1.0 |
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+ | 0.0891 | 14.0 | 42 | 0.4216 | 1.0 |
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+ | 0.0704 | 15.0 | 45 | 0.3880 | 1.0 |
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+ | 0.0505 | 16.0 | 48 | 0.3663 | 1.0 |
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+ | 0.0428 | 17.0 | 51 | 0.3536 | 1.0 |
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+ | 0.0356 | 18.0 | 54 | 0.3490 | 1.0 |
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+ | 0.0283 | 19.0 | 57 | 0.3531 | 1.0 |
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+ | 0.025 | 20.0 | 60 | 0.3595 | 1.0 |
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+ | 0.0239 | 21.0 | 63 | 0.3594 | 1.0 |
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+ | 0.0202 | 22.0 | 66 | 0.3521 | 1.0 |
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+ | 0.0168 | 23.0 | 69 | 0.3475 | 1.0 |
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+ | 0.0159 | 24.0 | 72 | 0.3458 | 1.0 |
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+ | 0.0164 | 25.0 | 75 | 0.3409 | 1.0 |
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+ | 0.0132 | 26.0 | 78 | 0.3360 | 1.0 |
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+ | 0.0137 | 27.0 | 81 | 0.3302 | 1.0 |
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+ | 0.0112 | 28.0 | 84 | 0.3235 | 1.0 |
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+ | 0.0113 | 29.0 | 87 | 0.3178 | 1.0 |
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+ | 0.0111 | 30.0 | 90 | 0.3159 | 1.0 |
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+ | 0.0113 | 31.0 | 93 | 0.3108 | 1.0 |
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+ | 0.0107 | 32.0 | 96 | 0.3101 | 1.0 |
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+ | 0.0101 | 33.0 | 99 | 0.3100 | 1.0 |
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+ | 0.0083 | 34.0 | 102 | 0.3110 | 1.0 |
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+ | 0.0092 | 35.0 | 105 | 0.3117 | 1.0 |
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+ | 0.0102 | 36.0 | 108 | 0.3104 | 1.0 |
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+ | 0.0086 | 37.0 | 111 | 0.3086 | 1.0 |
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+ | 0.0092 | 38.0 | 114 | 0.3047 | 1.0 |
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+ | 0.0072 | 39.0 | 117 | 0.3024 | 1.0 |
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+ | 0.0079 | 40.0 | 120 | 0.3014 | 1.0 |
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+ | 0.0079 | 41.0 | 123 | 0.2983 | 1.0 |
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+ | 0.0091 | 42.0 | 126 | 0.2948 | 1.0 |
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+ | 0.0077 | 43.0 | 129 | 0.2915 | 1.0 |
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+ | 0.0085 | 44.0 | 132 | 0.2890 | 1.0 |
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+ | 0.009 | 45.0 | 135 | 0.2870 | 1.0 |
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+ | 0.0073 | 46.0 | 138 | 0.2856 | 1.0 |
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+ | 0.0073 | 47.0 | 141 | 0.2844 | 1.0 |
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+ | 0.0076 | 48.0 | 144 | 0.2841 | 1.0 |
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+ | 0.0065 | 49.0 | 147 | 0.2836 | 1.0 |
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+ | 0.0081 | 50.0 | 150 | 0.2835 | 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