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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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metrics: |
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- rouge |
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model-index: |
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- name: Models |
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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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# Models |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Rouge1: 0.1065 |
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- Rouge2: 0.0421 |
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- Rougel: 0.0844 |
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- Rougelsum: 0.0844 |
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- Gen Len: 16.6846 |
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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: 4e-05 |
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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: 1 |
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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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| 0.0 | 0.1120 | 100 | nan | 0.1065 | 0.0421 | 0.0844 | 0.0844 | 16.6846 | |
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| 0.0 | 0.2240 | 200 | nan | 0.1065 | 0.0421 | 0.0844 | 0.0844 | 16.6846 | |
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| 0.0 | 0.3359 | 300 | nan | 0.1065 | 0.0421 | 0.0844 | 0.0844 | 16.6846 | |
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| 0.0 | 0.4479 | 400 | nan | 0.1065 | 0.0421 | 0.0844 | 0.0844 | 16.6846 | |
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| 0.0 | 0.5599 | 500 | nan | 0.1065 | 0.0421 | 0.0844 | 0.0844 | 16.6846 | |
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| 0.0 | 0.6719 | 600 | nan | 0.1065 | 0.0421 | 0.0844 | 0.0844 | 16.6846 | |
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| 0.0 | 0.7839 | 700 | nan | 0.1065 | 0.0421 | 0.0844 | 0.0844 | 16.6846 | |
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| 0.0 | 0.8959 | 800 | nan | 0.1065 | 0.0421 | 0.0844 | 0.0844 | 16.6846 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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