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--- |
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license: apache-2.0 |
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base_model: mHossain/ml_sum_v1 |
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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: ml_sum_v2 |
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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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# ml_sum_v2 |
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This model is a fine-tuned version of [mHossain/ml_sum_v1](https://huggingface.co/mHossain/ml_sum_v1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9401 |
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- Rouge1: 8.1448 |
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- Rouge2: 3.3615 |
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- Rougel: 7.4641 |
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- Rougelsum: 7.9361 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 5000 |
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- num_epochs: 5 |
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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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| No log | 1.0 | 312 | 2.1706 | 7.2919 | 2.8117 | 6.7418 | 7.1173 | 19.0 | |
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| 2.4911 | 2.0 | 625 | 2.1012 | 7.7986 | 3.0952 | 7.1505 | 7.5818 | 19.0 | |
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| 2.4911 | 3.0 | 937 | 2.0373 | 8.0535 | 3.2228 | 7.3877 | 7.8365 | 19.0 | |
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| 2.3572 | 4.0 | 1250 | 1.9865 | 8.1591 | 3.31 | 7.4577 | 7.9114 | 19.0 | |
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| 2.2455 | 4.99 | 1560 | 1.9401 | 8.1448 | 3.3615 | 7.4641 | 7.9361 | 19.0 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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