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README.md
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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_cola_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: cola
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split: validation
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args: cola
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.880859375
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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_cola_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: 0.3777
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- Accuracy: 0.8809
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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: 2
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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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| 0.5951 | 0.05 | 25 | 0.7088 | 0.6913 |
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| 0.5805 | 0.11 | 50 | 0.5398 | 0.6913 |
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| 0.5083 | 0.16 | 75 | 0.4858 | 0.8025 |
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| 0.4229 | 0.21 | 100 | 0.5415 | 0.7881 |
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| 0.4178 | 0.27 | 125 | 0.4968 | 0.7939 |
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| 0.4273 | 0.32 | 150 | 0.4996 | 0.8054 |
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| 0.4297 | 0.37 | 175 | 0.4798 | 0.8044 |
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| 0.4032 | 0.42 | 200 | 0.4975 | 0.8140 |
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| 0.4246 | 0.48 | 225 | 0.4489 | 0.8226 |
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| 0.4065 | 0.53 | 250 | 0.4677 | 0.8245 |
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| 0.4173 | 0.58 | 275 | 0.4121 | 0.8265 |
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| 0.3738 | 0.64 | 300 | 0.4524 | 0.8313 |
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| 0.3582 | 0.69 | 325 | 0.4726 | 0.8332 |
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| 0.3913 | 0.74 | 350 | 0.4031 | 0.8303 |
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| 0.3568 | 0.8 | 375 | 0.4740 | 0.8360 |
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| 0.337 | 0.85 | 400 | 0.4273 | 0.8322 |
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| 0.3437 | 0.9 | 425 | 0.4838 | 0.8370 |
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| 0.3879 | 0.96 | 450 | 0.4346 | 0.8360 |
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| 0.3248 | 1.01 | 475 | 0.4600 | 0.8370 |
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| 0.2341 | 1.06 | 500 | 0.5489 | 0.8370 |
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| 0.3 | 1.11 | 525 | 0.4724 | 0.8408 |
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| 0.1939 | 1.17 | 550 | 0.5440 | 0.8437 |
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| 0.2323 | 1.22 | 575 | 0.8830 | 0.8332 |
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| 0.2769 | 1.27 | 600 | 0.7055 | 0.8265 |
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| 0.1975 | 1.33 | 625 | 0.5484 | 0.8380 |
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| 0.2647 | 1.38 | 650 | 0.5763 | 0.8341 |
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| 0.225 | 1.43 | 675 | 0.5599 | 0.8351 |
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| 0.2835 | 1.49 | 700 | 0.6487 | 0.8313 |
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| 0.2591 | 1.54 | 725 | 0.5308 | 0.8332 |
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| 0.2751 | 1.59 | 750 | 0.4780 | 0.8332 |
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| 0.2602 | 1.65 | 775 | 0.4718 | 0.8389 |
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| 0.2315 | 1.7 | 800 | 0.5345 | 0.8313 |
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| 0.1938 | 1.75 | 825 | 0.5500 | 0.8332 |
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| 0.2507 | 1.8 | 850 | 0.5696 | 0.8322 |
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| 0.2734 | 1.86 | 875 | 0.5624 | 0.8303 |
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| 0.2917 | 1.91 | 900 | 0.5438 | 0.8303 |
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| 0.2492 | 1.96 | 925 | 0.5352 | 0.8313 |
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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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