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--- |
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base_model: ybelkada/flan-t5-xl-sharded-bf16 |
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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: flan-xl-gen6 |
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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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# flan-xl-gen6 |
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This model is a fine-tuned version of [ybelkada/flan-t5-xl-sharded-bf16](https://huggingface.co./ybelkada/flan-t5-xl-sharded-bf16) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4978 |
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- Rouge1: 29.5362 |
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- Rouge2: 20.6621 |
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- Rougel: 25.7689 |
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- Rougelsum: 26.2351 |
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- Gen Len: 12.7388 |
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 800 |
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- num_epochs: 8 |
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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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| No log | 1.0 | 328 | 0.6921 | 34.9112 | 26.7503 | 31.4124 | 31.7295 | 10.0172 | |
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| 6.8746 | 2.0 | 656 | 0.6025 | 33.9134 | 25.3236 | 30.1968 | 30.472 | 10.8454 | |
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| 6.8746 | 3.0 | 984 | 0.5687 | 31.6178 | 22.9463 | 27.8758 | 28.3572 | 11.8729 | |
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| 0.6462 | 4.0 | 1312 | 0.5355 | 30.8157 | 22.1783 | 27.1641 | 27.569 | 12.1306 | |
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| 0.5618 | 5.0 | 1640 | 0.5160 | 29.9183 | 21.0842 | 26.1671 | 26.5965 | 12.5017 | |
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| 0.5618 | 6.0 | 1968 | 0.5025 | 29.7823 | 21.1443 | 26.0286 | 26.5215 | 12.5086 | |
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| 0.498 | 7.0 | 2296 | 0.4978 | 29.1043 | 20.2391 | 25.3347 | 25.804 | 12.8969 | |
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| 0.4551 | 8.0 | 2624 | 0.4978 | 29.5362 | 20.6621 | 25.7689 | 26.2351 | 12.7388 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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