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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_dense_epochs-5 |
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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: train |
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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: 0.8813559322033898 |
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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_dense_epochs-5 |
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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: 0.4167 |
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- Accuracy: 0.8814 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 0 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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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: 5 |
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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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| 0.6749 | 0.19 | 10 | 0.6270 | 0.7095 | |
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| 0.5772 | 0.37 | 20 | 0.5947 | 0.7101 | |
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| 0.6066 | 0.56 | 30 | 0.5545 | 0.7101 | |
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| 0.5355 | 0.75 | 40 | 0.4788 | 0.7475 | |
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| 0.4398 | 0.93 | 50 | 0.3992 | 0.8469 | |
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| 0.3932 | 1.12 | 60 | 0.3737 | 0.8638 | |
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| 0.3756 | 1.31 | 70 | 0.3606 | 0.8650 | |
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| 0.4004 | 1.5 | 80 | 0.3645 | 0.8603 | |
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| 0.3198 | 1.68 | 90 | 0.3201 | 0.8749 | |
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| 0.3129 | 1.87 | 100 | 0.3638 | 0.8697 | |
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| 0.2763 | 2.06 | 110 | 0.3091 | 0.8819 | |
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| 0.3207 | 2.24 | 120 | 0.3781 | 0.8673 | |
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| 0.2614 | 2.43 | 130 | 0.3351 | 0.8773 | |
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| 0.2909 | 2.62 | 140 | 0.3404 | 0.8662 | |
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| 0.2899 | 2.8 | 150 | 0.3277 | 0.8796 | |
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| 0.2687 | 2.99 | 160 | 0.3520 | 0.8679 | |
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| 0.1993 | 3.18 | 170 | 0.3319 | 0.8854 | |
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| 0.2584 | 3.36 | 180 | 0.3901 | 0.8732 | |
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| 0.2502 | 3.55 | 190 | 0.3766 | 0.8773 | |
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| 0.2234 | 3.74 | 200 | 0.3360 | 0.8895 | |
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| 0.2101 | 3.93 | 210 | 0.3334 | 0.8849 | |
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| 0.1708 | 4.11 | 220 | 0.3819 | 0.8714 | |
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| 0.1664 | 4.3 | 230 | 0.3690 | 0.8773 | |
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| 0.2217 | 4.49 | 240 | 0.4181 | 0.8814 | |
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| 0.2034 | 4.67 | 250 | 0.3607 | 0.8796 | |
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| 0.1948 | 4.86 | 260 | 0.4167 | 0.8814 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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