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--- |
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license: apache-2.0 |
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base_model: t5-large |
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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: t5-large_sst2_sp0_ar0 |
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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 |
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type: glue |
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config: sst2 |
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split: validation |
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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: 0.9560546875 |
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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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# t5-large_sst2_sp0_ar0 |
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This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3456 |
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- Accuracy: 0.9561 |
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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: 16 |
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- eval_batch_size: 32 |
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- seed: 1 |
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- distributed_type: tpu |
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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: 20 |
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- training_steps: 750 |
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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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| 0.6852 | 0.01 | 25 | 0.6952 | 0.5092 | |
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| 0.6751 | 0.01 | 50 | 0.6331 | 0.7546 | |
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| 0.603 | 0.02 | 75 | 0.4811 | 0.8899 | |
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| 0.3459 | 0.02 | 100 | 0.2048 | 0.9335 | |
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| 0.1808 | 0.03 | 125 | 0.2377 | 0.9300 | |
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| 0.1933 | 0.04 | 150 | 0.3369 | 0.9323 | |
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| 0.527 | 0.04 | 175 | 0.6582 | 0.9404 | |
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| 0.2241 | 0.05 | 200 | 0.1874 | 0.9507 | |
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| 0.1997 | 0.05 | 225 | 0.5160 | 0.9472 | |
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| 0.2192 | 0.06 | 250 | 0.5193 | 0.9461 | |
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| 0.168 | 0.07 | 275 | 0.4091 | 0.9484 | |
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| 0.1879 | 0.07 | 300 | 0.3114 | 0.9427 | |
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| 0.1653 | 0.08 | 325 | 0.5526 | 0.9484 | |
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| 0.1847 | 0.08 | 350 | 0.6536 | 0.9450 | |
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| 0.1449 | 0.09 | 375 | 0.6520 | 0.9438 | |
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| 0.2485 | 0.1 | 400 | 0.4093 | 0.9518 | |
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| 0.1604 | 0.1 | 425 | 0.2821 | 0.9461 | |
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| 0.1316 | 0.11 | 450 | 0.8609 | 0.9461 | |
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| 0.1754 | 0.11 | 475 | 0.4047 | 0.9472 | |
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| 0.1524 | 0.12 | 500 | 0.4034 | 0.9495 | |
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| 0.4571 | 0.13 | 525 | 0.2895 | 0.9495 | |
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| 0.1448 | 0.13 | 550 | 0.5239 | 0.9484 | |
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| 0.1459 | 0.14 | 575 | 0.2996 | 0.9518 | |
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| 0.2131 | 0.14 | 600 | 0.2983 | 0.9495 | |
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| 0.1298 | 0.15 | 625 | 0.5322 | 0.9484 | |
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| 0.1519 | 0.16 | 650 | 0.5311 | 0.9518 | |
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| 0.1809 | 0.16 | 675 | 0.5271 | 0.9495 | |
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| 0.1495 | 0.17 | 700 | 0.5282 | 0.9495 | |
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| 0.1665 | 0.17 | 725 | 0.5307 | 0.9507 | |
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| 0.1978 | 0.18 | 750 | 0.5295 | 0.9507 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.11.6 |
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