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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_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: 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: 0.9575688073394495 |
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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_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: 0.6867 |
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- Accuracy: 0.9576 |
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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: 256 |
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- eval_batch_size: 256 |
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- seed: 0 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 512 |
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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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| 0.2069 | 0.38 | 50 | 0.4171 | 0.9438 | |
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| 0.1627 | 0.76 | 100 | 0.3713 | 0.9518 | |
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| 0.1641 | 1.14 | 150 | 0.4802 | 0.9553 | |
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| 0.1261 | 1.52 | 200 | 0.2517 | 0.9541 | |
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| 0.128 | 1.89 | 250 | 0.2427 | 0.9633 | |
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| 0.0765 | 2.27 | 300 | 0.5854 | 0.9622 | |
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| 0.1547 | 2.65 | 350 | 0.6896 | 0.9507 | |
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| 0.0705 | 3.03 | 400 | 0.5790 | 0.9484 | |
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| 0.0683 | 3.41 | 450 | 0.3680 | 0.9564 | |
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| 0.0889 | 3.79 | 500 | 0.6867 | 0.9576 | |
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| 0.1541 | 4.17 | 550 | 0.6979 | 0.9576 | |
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| 0.0689 | 4.55 | 600 | 0.9328 | 0.9507 | |
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| 0.0964 | 4.92 | 650 | 0.6852 | 0.9587 | |
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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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