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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: 0.9453125 |
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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: 0.1944 |
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- Accuracy: 0.9453 |
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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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- 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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- num_epochs: 6 |
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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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| 0.6815 | 0.01 | 25 | 0.6999 | 0.5092 | |
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| 0.6592 | 0.01 | 50 | 0.6221 | 0.6445 | |
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| 0.5832 | 0.02 | 75 | 0.4570 | 0.7993 | |
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| 0.2882 | 0.02 | 100 | 0.2076 | 0.9358 | |
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| 0.1894 | 0.03 | 125 | 0.3499 | 0.9404 | |
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| 0.1864 | 0.04 | 150 | 0.2963 | 0.9461 | |
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| 0.2553 | 0.04 | 175 | 0.6929 | 0.9289 | |
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| 0.245 | 0.05 | 200 | 0.4761 | 0.9323 | |
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| 0.2042 | 0.05 | 225 | 0.5294 | 0.9461 | |
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| 0.2002 | 0.06 | 250 | 0.8441 | 0.9472 | |
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| 0.1633 | 0.07 | 275 | 0.8560 | 0.9495 | |
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| 0.1939 | 0.07 | 300 | 0.3197 | 0.9450 | |
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| 0.1928 | 0.08 | 325 | 0.4214 | 0.9472 | |
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| 0.2201 | 0.08 | 350 | 0.5266 | 0.9484 | |
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| 0.143 | 0.09 | 375 | 0.8642 | 0.9450 | |
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| 0.2354 | 0.1 | 400 | 1.2116 | 0.9335 | |
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| 0.1692 | 0.1 | 425 | 0.1807 | 0.9472 | |
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| 0.1531 | 0.11 | 450 | 0.6431 | 0.9484 | |
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| 0.152 | 0.11 | 475 | 1.4046 | 0.9553 | |
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| 0.1948 | 0.12 | 500 | 0.1596 | 0.9553 | |
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| 0.2007 | 0.13 | 525 | 0.1779 | 0.9438 | |
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| 0.1338 | 0.13 | 550 | 0.6476 | 0.9495 | |
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| 0.3812 | 0.14 | 575 | 0.3901 | 0.9484 | |
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| 0.7052 | 0.14 | 600 | 0.1740 | 0.9507 | |
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| 0.8601 | 0.15 | 625 | 1.5226 | 0.9484 | |
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| 1.384 | 0.16 | 650 | 0.6605 | 0.9427 | |
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| 0.6833 | 0.16 | 675 | 0.7313 | 0.9484 | |
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| 0.1833 | 0.17 | 700 | 0.4110 | 0.9438 | |
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| 0.1968 | 0.17 | 725 | 0.2914 | 0.9450 | |
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| 0.2001 | 0.18 | 750 | 0.1947 | 0.9335 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.11.6 |
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