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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- neulab/tldr |
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metrics: |
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- rouge |
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model-index: |
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- name: BASH-Coder-Flan-T5-base |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: tldr |
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type: tldr |
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config: data |
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split: validation |
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args: data |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 27.0741 |
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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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# BASH-Coder-Flan-T5-base |
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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 [neulab/tldr](https://huggingface.co/datasets/neulab/tldr) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3608 |
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- Rouge1: 27.0741 |
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- Rouge2: 9.3824 |
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- Rougel: 26.133 |
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- Rougelsum: 26.1559 |
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- Gen Len: 15.5767 |
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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: 8 |
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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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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 10 |
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- label_smoothing_factor: 0.1 |
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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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| 4.3554 | 1.0 | 802 | 3.5928 | 22.7234 | 6.7951 | 22.0647 | 22.0744 | 15.2363 | |
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| 3.5335 | 2.0 | 1604 | 3.4654 | 25.7842 | 8.5847 | 24.8207 | 24.8808 | 15.168 | |
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| 3.3341 | 3.0 | 2406 | 3.4078 | 25.5756 | 8.4456 | 24.706 | 24.7207 | 15.6472 | |
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| 3.2011 | 4.0 | 3208 | 3.3789 | 26.0638 | 8.6853 | 25.0862 | 25.1223 | 16.2748 | |
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| 3.1059 | 5.0 | 4010 | 3.3622 | 26.7254 | 9.1138 | 25.7985 | 25.8521 | 15.7366 | |
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| 3.0336 | 6.0 | 4812 | 3.3662 | 26.4655 | 9.1283 | 25.4587 | 25.5112 | 16.548 | |
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| 2.9727 | 7.0 | 5614 | 3.3593 | 26.8211 | 9.3045 | 25.8497 | 25.8772 | 15.5431 | |
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| 2.9298 | 8.0 | 6416 | 3.3643 | 26.8932 | 9.3537 | 25.9444 | 26.0088 | 15.916 | |
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| 2.9005 | 9.0 | 7218 | 3.3606 | 27.1732 | 9.5661 | 26.1198 | 26.1515 | 15.71 | |
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| 2.8846 | 10.0 | 8020 | 3.3608 | 27.0741 | 9.3824 | 26.133 | 26.1559 | 15.5767 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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## Finr-tuning Script |
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[Google Colaboratory Notebook](https://colab.research.google.com/drive/1VMSVa49xn6O-P6CGNd5AOSoGkPV8D2F_?usp=sharing) |
