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--- |
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language: |
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- en |
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base_model: google-t5/t5-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: SST2 |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: GLUE SST2 |
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type: glue |
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args: sst2 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.948394495412844 |
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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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# SST2 |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the GLUE SST2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2225 |
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- Accuracy: 0.9484 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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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: 10.0 |
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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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| 0.1443 | 1.0 | 2105 | 0.2072 | 0.9323 | |
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| 0.1152 | 2.0 | 4210 | 0.2127 | 0.9404 | |
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| 0.0849 | 3.0 | 6315 | 0.2156 | 0.9438 | |
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| 0.0709 | 4.0 | 8420 | 0.2225 | 0.9484 | |
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| 0.06 | 5.0 | 10525 | 0.2719 | 0.9404 | |
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| 0.0507 | 6.0 | 12630 | 0.2911 | 0.9404 | |
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| 0.0435 | 7.0 | 14735 | 0.3279 | 0.9335 | |
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| 0.0357 | 8.0 | 16840 | 0.3566 | 0.9312 | |
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| 0.0274 | 9.0 | 18945 | 0.3876 | 0.9358 | |
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| 0.0253 | 10.0 | 21050 | 0.4034 | 0.9381 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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