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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-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: TrainedSentiment |
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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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# TrainedSentiment |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 0.0299 |
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- Accuracy: 0.9833 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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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 | 38 | 0.6023 | 0.6233 | |
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| No log | 2.0 | 76 | 0.4643 | 0.7883 | |
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| No log | 3.0 | 114 | 0.4152 | 0.8233 | |
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| No log | 4.0 | 152 | 0.2017 | 0.93 | |
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| No log | 5.0 | 190 | 0.1128 | 0.9617 | |
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| No log | 6.0 | 228 | 0.0679 | 0.9767 | |
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| No log | 7.0 | 266 | 0.0548 | 0.9783 | |
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| No log | 8.0 | 304 | 0.0476 | 0.98 | |
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| No log | 9.0 | 342 | 0.0460 | 0.9817 | |
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| No log | 10.0 | 380 | 0.0414 | 0.9833 | |
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| No log | 11.0 | 418 | 0.0414 | 0.9817 | |
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| No log | 12.0 | 456 | 0.0387 | 0.9817 | |
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| No log | 13.0 | 494 | 0.0377 | 0.9833 | |
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| 0.2188 | 14.0 | 532 | 0.0353 | 0.9833 | |
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| 0.2188 | 15.0 | 570 | 0.0329 | 0.9833 | |
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| 0.2188 | 16.0 | 608 | 0.0314 | 0.985 | |
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| 0.2188 | 17.0 | 646 | 0.0308 | 0.985 | |
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| 0.2188 | 18.0 | 684 | 0.0300 | 0.985 | |
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| 0.2188 | 19.0 | 722 | 0.0297 | 0.985 | |
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| 0.2188 | 20.0 | 760 | 0.0299 | 0.9833 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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