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--- |
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license: apache-2.0 |
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base_model: facebook/bart-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Bart-base-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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# Bart-base-v2 |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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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: 3 |
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- eval_batch_size: 3 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 12 |
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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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 985982.912 | 0.24 | 250 | nan | |
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| 0.0 | 0.48 | 500 | nan | |
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| 0.0 | 0.72 | 750 | nan | |
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| 0.0 | 0.96 | 1000 | nan | |
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| 0.0 | 1.2 | 1250 | nan | |
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| 0.0 | 1.44 | 1500 | nan | |
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| 0.0 | 1.69 | 1750 | nan | |
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| 0.0 | 1.93 | 2000 | nan | |
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| 0.0 | 2.17 | 2250 | nan | |
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| 0.0 | 2.41 | 2500 | nan | |
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| 0.0 | 2.65 | 2750 | nan | |
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| 0.0 | 2.89 | 3000 | nan | |
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| 0.0 | 3.13 | 3250 | nan | |
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| 0.0 | 3.37 | 3500 | nan | |
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| 0.0 | 3.61 | 3750 | nan | |
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| 0.0 | 3.85 | 4000 | nan | |
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| 0.0 | 4.09 | 4250 | nan | |
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| 0.0 | 4.33 | 4500 | nan | |
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| 0.0 | 4.57 | 4750 | nan | |
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| 0.0 | 4.81 | 5000 | nan | |
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| 0.0 | 5.06 | 5250 | nan | |
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| 0.0 | 5.3 | 5500 | nan | |
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| 0.0 | 5.54 | 5750 | nan | |
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| 0.0 | 5.78 | 6000 | nan | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.2 |
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