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--- |
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license: apache-2.0 |
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base_model: t5-3b |
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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: t5-3b_rte_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: rte |
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split: validation |
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args: rte |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8995983935742972 |
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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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# t5-3b_rte_sp0_ar0 |
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This model is a fine-tuned version of [t5-3b](https://huggingface.co/t5-3b) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4886 |
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- Accuracy: 0.8996 |
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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: 16 |
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- seed: 1 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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| 0.7116 | 0.18 | 25 | 0.7078 | 0.4838 | |
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| 0.615 | 0.36 | 50 | 0.4571 | 0.8484 | |
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| 0.501 | 0.53 | 75 | 0.4176 | 0.8484 | |
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| 0.337 | 0.71 | 100 | 0.4462 | 0.8809 | |
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| 0.4199 | 0.89 | 125 | 0.4309 | 0.7942 | |
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| 0.2477 | 1.07 | 150 | 0.4325 | 0.8881 | |
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| 0.2253 | 1.25 | 175 | 0.4596 | 0.8845 | |
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| 0.214 | 1.42 | 200 | 0.9106 | 0.8736 | |
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| 0.2577 | 1.6 | 225 | 0.3652 | 0.9025 | |
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| 0.1966 | 1.78 | 250 | 0.3645 | 0.9097 | |
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| 0.2278 | 1.96 | 275 | 0.3337 | 0.9206 | |
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| 0.1221 | 2.14 | 300 | 1.2373 | 0.8881 | |
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| 0.3576 | 2.31 | 325 | 2.0514 | 0.8809 | |
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| 0.6186 | 2.49 | 350 | 3.9886 | 0.8809 | |
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| 1.0915 | 2.67 | 375 | 3.3403 | 0.8845 | |
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| 0.321 | 2.85 | 400 | 4.6906 | 0.8989 | |
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| 0.3969 | 3.02 | 425 | 1.2608 | 0.8736 | |
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| 0.026 | 3.2 | 450 | 4.4563 | 0.8809 | |
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| 0.0695 | 3.38 | 475 | 4.6858 | 0.8917 | |
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| 0.7626 | 3.56 | 500 | 4.7502 | 0.8917 | |
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| 0.2675 | 3.74 | 525 | 5.0576 | 0.9025 | |
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| 0.82 | 3.91 | 550 | 3.6297 | 0.9025 | |
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| 0.0011 | 4.09 | 575 | 5.7629 | 0.8989 | |
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| 0.3 | 4.27 | 600 | 2.3117 | 0.9097 | |
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| 0.0544 | 4.45 | 625 | 1.5657 | 0.9097 | |
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| 0.2907 | 4.63 | 650 | 2.6475 | 0.9025 | |
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| 0.2868 | 4.8 | 675 | 2.6720 | 0.8989 | |
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| 0.3191 | 4.98 | 700 | 2.8372 | 0.8773 | |
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| 0.0382 | 5.16 | 725 | 6.0565 | 0.9025 | |
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| 0.0297 | 5.34 | 750 | 4.1639 | 0.8736 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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