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deberta-v3-large__sst2__train-8-6

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deberta-v2
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+ ---
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+ license: mit
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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: deberta-v3-large__sst2__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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+ # deberta-v3-large__sst2__train-8-6
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.4331
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+ - Accuracy: 0.7106
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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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+ | 0.6486 | 1.0 | 3 | 0.7901 | 0.25 |
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+ | 0.6418 | 2.0 | 6 | 0.9259 | 0.25 |
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+ | 0.6169 | 3.0 | 9 | 1.0574 | 0.25 |
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+ | 0.5639 | 4.0 | 12 | 1.1372 | 0.25 |
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+ | 0.4562 | 5.0 | 15 | 0.6090 | 0.5 |
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+ | 0.3105 | 6.0 | 18 | 0.4435 | 1.0 |
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+ | 0.2303 | 7.0 | 21 | 0.2804 | 1.0 |
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+ | 0.1388 | 8.0 | 24 | 0.2205 | 1.0 |
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+ | 0.0918 | 9.0 | 27 | 0.1282 | 1.0 |
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+ | 0.0447 | 10.0 | 30 | 0.0643 | 1.0 |
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+ | 0.0297 | 11.0 | 33 | 0.0361 | 1.0 |
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+ | 0.0159 | 12.0 | 36 | 0.0211 | 1.0 |
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+ | 0.0102 | 13.0 | 39 | 0.0155 | 1.0 |
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+ | 0.0061 | 14.0 | 42 | 0.0158 | 1.0 |
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+ | 0.0049 | 15.0 | 45 | 0.0189 | 1.0 |
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+ | 0.0035 | 16.0 | 48 | 0.0254 | 1.0 |
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+ | 0.0027 | 17.0 | 51 | 0.0305 | 1.0 |
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+ | 0.0021 | 18.0 | 54 | 0.0287 | 1.0 |
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+ | 0.0016 | 19.0 | 57 | 0.0215 | 1.0 |
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+ | 0.0016 | 20.0 | 60 | 0.0163 | 1.0 |
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+ | 0.0014 | 21.0 | 63 | 0.0138 | 1.0 |
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+ | 0.0015 | 22.0 | 66 | 0.0131 | 1.0 |
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+ | 0.001 | 23.0 | 69 | 0.0132 | 1.0 |
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+ | 0.0014 | 24.0 | 72 | 0.0126 | 1.0 |
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+ | 0.0011 | 25.0 | 75 | 0.0125 | 1.0 |
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+ | 0.001 | 26.0 | 78 | 0.0119 | 1.0 |
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+ | 0.0008 | 27.0 | 81 | 0.0110 | 1.0 |
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+ | 0.0007 | 28.0 | 84 | 0.0106 | 1.0 |
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+ | 0.0008 | 29.0 | 87 | 0.0095 | 1.0 |
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+ | 0.0009 | 30.0 | 90 | 0.0089 | 1.0 |
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+ | 0.0008 | 31.0 | 93 | 0.0083 | 1.0 |
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+ | 0.0007 | 32.0 | 96 | 0.0075 | 1.0 |
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+ | 0.0008 | 33.0 | 99 | 0.0066 | 1.0 |
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+ | 0.0006 | 34.0 | 102 | 0.0059 | 1.0 |
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+ | 0.0007 | 35.0 | 105 | 0.0054 | 1.0 |
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+ | 0.0008 | 36.0 | 108 | 0.0051 | 1.0 |
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+ | 0.0007 | 37.0 | 111 | 0.0049 | 1.0 |
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+ | 0.0007 | 38.0 | 114 | 0.0047 | 1.0 |
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+ | 0.0006 | 39.0 | 117 | 0.0045 | 1.0 |
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+ | 0.0006 | 40.0 | 120 | 0.0046 | 1.0 |
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+ | 0.0005 | 41.0 | 123 | 0.0045 | 1.0 |
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+ | 0.0006 | 42.0 | 126 | 0.0044 | 1.0 |
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+ | 0.0006 | 43.0 | 129 | 0.0043 | 1.0 |
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+ | 0.0006 | 44.0 | 132 | 0.0044 | 1.0 |
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+ | 0.0005 | 45.0 | 135 | 0.0045 | 1.0 |
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+ | 0.0006 | 46.0 | 138 | 0.0043 | 1.0 |
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+ | 0.0006 | 47.0 | 141 | 0.0043 | 1.0 |
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+ | 0.0006 | 48.0 | 144 | 0.0041 | 1.0 |
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+ | 0.0007 | 49.0 | 147 | 0.0042 | 1.0 |
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+ | 0.0005 | 50.0 | 150 | 0.0042 | 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