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--- |
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license: apache-2.0 |
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base_model: t5-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- sst |
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model-index: |
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- name: sst-t5-base |
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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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# sst-t5-base |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the sst dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0185 |
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- Mse: 0.0185 |
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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: 8 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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 | Mse | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 267 | 0.0196 | 0.0196 | |
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| 0.0237 | 2.0 | 534 | 0.0179 | 0.0179 | |
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| 0.0237 | 3.0 | 801 | 0.0174 | 0.0174 | |
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| 0.0133 | 4.0 | 1068 | 0.0182 | 0.0182 | |
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| 0.0133 | 5.0 | 1335 | 0.0181 | 0.0181 | |
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| 0.0101 | 6.0 | 1602 | 0.0180 | 0.0180 | |
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| 0.0101 | 7.0 | 1869 | 0.0183 | 0.0183 | |
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| 0.0083 | 8.0 | 2136 | 0.0188 | 0.0188 | |
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| 0.0083 | 9.0 | 2403 | 0.0185 | 0.0186 | |
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| 0.0067 | 10.0 | 2670 | 0.0187 | 0.0187 | |
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| 0.0067 | 11.0 | 2937 | 0.0184 | 0.0184 | |
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| 0.0057 | 12.0 | 3204 | 0.0186 | 0.0186 | |
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| 0.0057 | 13.0 | 3471 | 0.0194 | 0.0194 | |
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| 0.005 | 14.0 | 3738 | 0.0175 | 0.0176 | |
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| 0.0045 | 15.0 | 4005 | 0.0182 | 0.0182 | |
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| 0.0045 | 16.0 | 4272 | 0.0183 | 0.0183 | |
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| 0.0041 | 17.0 | 4539 | 0.0187 | 0.0187 | |
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| 0.0041 | 18.0 | 4806 | 0.0186 | 0.0186 | |
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| 0.0038 | 19.0 | 5073 | 0.0188 | 0.0188 | |
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| 0.0038 | 20.0 | 5340 | 0.0185 | 0.0185 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.2 |
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