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--- |
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license: mit |
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base_model: gpt2-medium |
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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: gpt2-medium-supervised-summarize-checkpoint |
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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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# gpt2-medium-supervised-summarize-checkpoint |
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This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7422 |
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- Rouge1: 0.6035 |
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- Rouge2: 0.2047 |
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- Rougel: 0.4141 |
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- Rougelsum: 0.5319 |
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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: 1e-05 |
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- train_batch_size: 50 |
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- eval_batch_size: 50 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- optimizer: Adam with betas=(0.9,0.95) 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: 2 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| 1.859 | 0.21 | 500 | 1.8105 | 0.5966 | 0.1961 | 0.4025 | 0.5237 | |
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| 1.852 | 0.43 | 1000 | 1.7900 | 0.5994 | 0.1981 | 0.4061 | 0.5271 | |
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| 1.8189 | 0.64 | 1500 | 1.7764 | 0.6000 | 0.2005 | 0.4082 | 0.5276 | |
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| 1.8191 | 0.86 | 2000 | 1.7695 | 0.6013 | 0.2009 | 0.4096 | 0.5290 | |
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| 1.7969 | 1.07 | 2500 | 1.7617 | 0.6038 | 0.2020 | 0.4108 | 0.5311 | |
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| 1.7967 | 1.28 | 3000 | 1.7578 | 0.6024 | 0.2024 | 0.4114 | 0.5304 | |
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| 1.7813 | 1.5 | 3500 | 1.7520 | 0.6038 | 0.2039 | 0.4128 | 0.5320 | |
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| 1.7704 | 1.71 | 4000 | 1.7480 | 0.6033 | 0.2045 | 0.4132 | 0.5310 | |
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| 1.7852 | 1.93 | 4500 | 1.7422 | 0.6035 | 0.2047 | 0.4141 | 0.5319 | |
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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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