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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-base-devices-sum-ver1 |
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results: [] |
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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-base-devices-sum-ver1 |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0935 |
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- Rouge1: 97.2294 |
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- Rouge2: 80.1323 |
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- Rougel: 97.245 |
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- Rougelsum: 97.2763 |
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- Gen Len: 4.9507 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| No log | 1.0 | 186 | 0.2461 | 91.9436 | 71.232 | 91.9417 | 91.9585 | 4.6644 | |
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| No log | 2.0 | 372 | 0.1580 | 94.5247 | 76.1321 | 94.5044 | 94.5382 | 4.8953 | |
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| 0.488 | 3.0 | 558 | 0.1239 | 95.8673 | 78.1183 | 95.8862 | 95.8919 | 4.9102 | |
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| 0.488 | 4.0 | 744 | 0.1100 | 96.5746 | 78.9878 | 96.5848 | 96.5831 | 4.9102 | |
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| 0.488 | 5.0 | 930 | 0.1008 | 96.9074 | 79.5536 | 96.9143 | 96.9317 | 4.9291 | |
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| 0.1303 | 6.0 | 1116 | 0.0974 | 96.9274 | 79.6953 | 96.933 | 96.9473 | 4.9291 | |
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| 0.1303 | 7.0 | 1302 | 0.0969 | 96.8041 | 79.5073 | 96.817 | 96.8266 | 4.9271 | |
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| 0.1303 | 8.0 | 1488 | 0.0945 | 97.1496 | 79.9757 | 97.1529 | 97.1779 | 4.9534 | |
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| 0.089 | 9.0 | 1674 | 0.0944 | 97.253 | 80.1236 | 97.2619 | 97.2899 | 4.9595 | |
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| 0.089 | 10.0 | 1860 | 0.0935 | 97.2294 | 80.1323 | 97.245 | 97.2763 | 4.9507 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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