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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: |
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- xsum |
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metrics: |
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- rouge |
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base_model: google/flan-t5-base |
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model-index: |
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- name: flan-t5-base-xsum |
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results: |
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- task: |
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type: text2text-generation |
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name: Sequence-to-sequence Language Modeling |
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dataset: |
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name: xsum |
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type: xsum |
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config: default |
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split: test |
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args: default |
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metrics: |
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- type: rouge |
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value: 32.3503 |
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name: Rouge1 |
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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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# flan-t5-base-xsum |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the xsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0798 |
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- Rouge1: 32.3503 |
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- Rouge2: 10.8909 |
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- Rougel: 25.9346 |
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- Rougelsum: 25.9216 |
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- Gen Len: 18.8494 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adafactor |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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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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| 2.335 | 1.0 | 1417 | 2.0823 | 31.3453 | 10.2077 | 25.0051 | 25.008 | 18.8259 | |
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| 1.8642 | 2.0 | 2834 | 2.0798 | 32.3503 | 10.8909 | 25.9346 | 25.9216 | 18.8494 | |
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| 1.5208 | 3.0 | 4251 | 2.1272 | 32.6743 | 11.3394 | 26.3776 | 26.3724 | 18.8435 | |
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| 1.2628 | 4.0 | 5668 | 2.2110 | 32.695 | 11.3273 | 26.3215 | 26.322 | 18.8306 | |
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| 1.0649 | 5.0 | 7085 | 2.3143 | 32.5287 | 11.3662 | 26.274 | 26.2741 | 18.8345 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.0 |
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- Tokenizers 0.13.2 |
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