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--- |
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license: mit |
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base_model: roberta-large |
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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: roberta-large-sst-2-16-13-smoothed |
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results: [] |
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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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# roberta-large-sst-2-16-13-smoothed |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6487 |
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- Accuracy: 0.75 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 50 |
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- num_epochs: 75 |
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- label_smoothing_factor: 0.45 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 1 | 0.7106 | 0.5 | |
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| No log | 2.0 | 2 | 0.7104 | 0.5 | |
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| No log | 3.0 | 3 | 0.7100 | 0.5 | |
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| No log | 4.0 | 4 | 0.7094 | 0.5 | |
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| No log | 5.0 | 5 | 0.7087 | 0.5 | |
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| No log | 6.0 | 6 | 0.7077 | 0.5 | |
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| No log | 7.0 | 7 | 0.7066 | 0.5 | |
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| No log | 8.0 | 8 | 0.7054 | 0.5 | |
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| No log | 9.0 | 9 | 0.7040 | 0.5 | |
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| 0.7172 | 10.0 | 10 | 0.7026 | 0.5 | |
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| 0.7172 | 11.0 | 11 | 0.7011 | 0.5 | |
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| 0.7172 | 12.0 | 12 | 0.6995 | 0.5 | |
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| 0.7172 | 13.0 | 13 | 0.6980 | 0.5 | |
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| 0.7172 | 14.0 | 14 | 0.6965 | 0.5312 | |
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| 0.7172 | 15.0 | 15 | 0.6951 | 0.5312 | |
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| 0.7172 | 16.0 | 16 | 0.6936 | 0.5312 | |
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| 0.7172 | 17.0 | 17 | 0.6921 | 0.5312 | |
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| 0.7172 | 18.0 | 18 | 0.6906 | 0.5312 | |
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| 0.7172 | 19.0 | 19 | 0.6895 | 0.5312 | |
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| 0.6997 | 20.0 | 20 | 0.6884 | 0.5312 | |
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| 0.6997 | 21.0 | 21 | 0.6874 | 0.5312 | |
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| 0.6997 | 22.0 | 22 | 0.6867 | 0.5625 | |
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| 0.6997 | 23.0 | 23 | 0.6860 | 0.5312 | |
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| 0.6997 | 24.0 | 24 | 0.6854 | 0.5938 | |
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| 0.6997 | 25.0 | 25 | 0.6846 | 0.6562 | |
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| 0.6997 | 26.0 | 26 | 0.6840 | 0.625 | |
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| 0.6997 | 27.0 | 27 | 0.6832 | 0.6562 | |
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| 0.6997 | 28.0 | 28 | 0.6826 | 0.6875 | |
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| 0.6997 | 29.0 | 29 | 0.6815 | 0.6875 | |
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| 0.6874 | 30.0 | 30 | 0.6804 | 0.6875 | |
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| 0.6874 | 31.0 | 31 | 0.6790 | 0.6875 | |
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| 0.6874 | 32.0 | 32 | 0.6772 | 0.6875 | |
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| 0.6874 | 33.0 | 33 | 0.6762 | 0.6562 | |
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| 0.6874 | 34.0 | 34 | 0.6753 | 0.6562 | |
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| 0.6874 | 35.0 | 35 | 0.6738 | 0.6875 | |
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| 0.6874 | 36.0 | 36 | 0.6725 | 0.6875 | |
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| 0.6874 | 37.0 | 37 | 0.6696 | 0.6875 | |
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| 0.6874 | 38.0 | 38 | 0.6687 | 0.6875 | |
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| 0.6874 | 39.0 | 39 | 0.6665 | 0.6875 | |
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| 0.6594 | 40.0 | 40 | 0.6643 | 0.6875 | |
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| 0.6594 | 41.0 | 41 | 0.6674 | 0.6875 | |
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| 0.6594 | 42.0 | 42 | 0.6733 | 0.6875 | |
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| 0.6594 | 43.0 | 43 | 0.6804 | 0.6875 | |
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| 0.6594 | 44.0 | 44 | 0.6731 | 0.6875 | |
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| 0.6594 | 45.0 | 45 | 0.6701 | 0.6875 | |
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| 0.6594 | 46.0 | 46 | 0.6687 | 0.6875 | |
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| 0.6594 | 47.0 | 47 | 0.6687 | 0.6562 | |
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| 0.6594 | 48.0 | 48 | 0.6757 | 0.625 | |
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| 0.6594 | 49.0 | 49 | 0.6739 | 0.6875 | |
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| 0.6089 | 50.0 | 50 | 0.6766 | 0.6875 | |
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| 0.6089 | 51.0 | 51 | 0.6724 | 0.6875 | |
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| 0.6089 | 52.0 | 52 | 0.6662 | 0.6875 | |
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| 0.6089 | 53.0 | 53 | 0.6664 | 0.6875 | |
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| 0.6089 | 54.0 | 54 | 0.6602 | 0.6875 | |
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| 0.6089 | 55.0 | 55 | 0.6505 | 0.6875 | |
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| 0.6089 | 56.0 | 56 | 0.6468 | 0.75 | |
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| 0.6089 | 57.0 | 57 | 0.6370 | 0.75 | |
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| 0.6089 | 58.0 | 58 | 0.6285 | 0.7812 | |
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| 0.6089 | 59.0 | 59 | 0.6267 | 0.7812 | |
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| 0.5694 | 60.0 | 60 | 0.6279 | 0.7812 | |
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| 0.5694 | 61.0 | 61 | 0.6364 | 0.7812 | |
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| 0.5694 | 62.0 | 62 | 0.6443 | 0.75 | |
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| 0.5694 | 63.0 | 63 | 0.6518 | 0.7812 | |
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| 0.5694 | 64.0 | 64 | 0.6634 | 0.7188 | |
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| 0.5694 | 65.0 | 65 | 0.6647 | 0.7188 | |
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| 0.5694 | 66.0 | 66 | 0.6679 | 0.7188 | |
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| 0.5694 | 67.0 | 67 | 0.6669 | 0.7188 | |
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| 0.5694 | 68.0 | 68 | 0.6626 | 0.7188 | |
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| 0.5694 | 69.0 | 69 | 0.6624 | 0.75 | |
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| 0.5618 | 70.0 | 70 | 0.6614 | 0.7188 | |
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| 0.5618 | 71.0 | 71 | 0.6592 | 0.75 | |
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| 0.5618 | 72.0 | 72 | 0.6571 | 0.75 | |
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| 0.5618 | 73.0 | 73 | 0.6541 | 0.75 | |
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| 0.5618 | 74.0 | 74 | 0.6499 | 0.75 | |
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| 0.5618 | 75.0 | 75 | 0.6487 | 0.75 | |
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### Framework versions |
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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 |
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