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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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datasets: |
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- arxiv-summarization |
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metrics: |
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- rouge |
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base_model: google/long-t5-tglobal-base |
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model-index: |
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- name: longt5-arvix-finetuned |
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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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# longt5-arvix-finetuned |
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This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the arxiv-summarization dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 30.0035 |
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- Rouge1: 0.0875 |
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- Rouge2: 0.0242 |
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- Rougel: 0.0708 |
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- Rougelsum: 0.0709 |
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- Gen Len: 19.0 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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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### 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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| 29.9697 | 1.0 | 1015 | 31.5396 | 0.089 | 0.0243 | 0.072 | 0.072 | 19.0 | |
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| 26.9874 | 2.0 | 2031 | 30.1941 | 0.0879 | 0.0242 | 0.0711 | 0.0712 | 19.0 | |
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| 26.6468 | 3.0 | 3046 | 30.0299 | 0.0877 | 0.0243 | 0.071 | 0.0712 | 19.0 | |
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| 26.4548 | 4.0 | 4062 | 30.0120 | 0.087 | 0.0239 | 0.0704 | 0.0705 | 19.0 | |
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| 26.5997 | 5.0 | 5077 | 30.0093 | 0.0875 | 0.0241 | 0.0708 | 0.0709 | 19.0 | |
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| 26.411 | 6.0 | 6093 | 30.0050 | 0.0875 | 0.024 | 0.0709 | 0.0709 | 19.0 | |
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| 26.5478 | 7.0 | 7108 | 30.0062 | 0.0876 | 0.0242 | 0.071 | 0.0711 | 19.0 | |
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| 26.4063 | 8.0 | 8124 | 30.0035 | 0.0876 | 0.0242 | 0.071 | 0.071 | 19.0 | |
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| 26.4737 | 9.0 | 9139 | 30.0070 | 0.0874 | 0.0241 | 0.0708 | 0.0709 | 19.0 | |
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| 26.5836 | 10.0 | 10150 | 30.0035 | 0.0875 | 0.0242 | 0.0708 | 0.0709 | 19.0 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
