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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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datasets: din0s/asqa |
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metrics: |
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- rouge |
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base_model: google/t5-small-ssm-nq |
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model-index: |
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- name: t5-small-asqa-ob |
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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-small-asqa-ob |
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This model is a fine-tuned version of [google/t5-small-ssm-nq](https://huggingface.co/google/t5-small-ssm-nq) on the [ASQA](https://huggingface.co/datasets/din0s/asqa) dataset without context (closed book). |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8099 |
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- Rouge1: 0.1493 |
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- Rouge2: 0.0837 |
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- Rougel: 0.1272 |
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- Rougelsum: 0.1270 |
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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: 0.0005 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| 3.8208 | 1.0 | 710 | 2.7856 | 0.1267 | 0.0644 | 0.1086 | 0.1084 | |
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| 3.0532 | 2.0 | 1420 | 2.6247 | 0.1321 | 0.0721 | 0.1145 | 0.1144 | |
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| 2.5656 | 3.0 | 2130 | 2.5062 | 0.1399 | 0.0773 | 0.1213 | 0.1213 | |
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| 2.3806 | 4.0 | 2840 | 2.5004 | 0.1431 | 0.0805 | 0.1243 | 0.1241 | |
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| 2.157 | 5.0 | 3550 | 2.5008 | 0.1455 | 0.0808 | 0.1255 | 0.1254 | |
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| 2.0458 | 6.0 | 4260 | 2.5313 | 0.1510 | 0.0846 | 0.1303 | 0.1301 | |
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| 1.914 | 7.0 | 4970 | 2.5298 | 0.1585 | 0.0885 | 0.1361 | 0.1358 | |
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| 1.7479 | 8.0 | 5680 | 2.5832 | 0.1508 | 0.0844 | 0.1292 | 0.1291 | |
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| 1.6875 | 9.0 | 6390 | 2.5928 | 0.1493 | 0.0834 | 0.1281 | 0.1279 | |
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| 1.574 | 10.0 | 7100 | 2.6364 | 0.1591 | 0.0885 | 0.1364 | 0.1363 | |
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| 1.4554 | 11.0 | 7810 | 2.6978 | 0.1513 | 0.0849 | 0.1295 | 0.1295 | |
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| 1.3909 | 12.0 | 8520 | 2.8099 | 0.1493 | 0.0837 | 0.1272 | 0.1270 | |
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### Framework versions |
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- Transformers 4.23.0.dev0 |
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- Pytorch 1.12.1+cu102 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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