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--- |
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library_name: transformers |
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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: results |
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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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# results |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7266 |
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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: 4 |
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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: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.8268 | 0.08 | 1000 | 0.7354 | |
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| 0.7977 | 0.16 | 2000 | 0.7251 | |
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| 0.7739 | 0.24 | 3000 | 0.7259 | |
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| 0.771 | 0.32 | 4000 | 0.7269 | |
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| 0.7468 | 0.4 | 5000 | 0.7269 | |
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| 0.751 | 0.48 | 6000 | 0.7501 | |
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| 0.7483 | 0.56 | 7000 | 0.7502 | |
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| 0.7443 | 0.64 | 8000 | 0.7253 | |
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| 0.7294 | 0.72 | 9000 | 0.7309 | |
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| 0.7309 | 0.8 | 10000 | 0.7260 | |
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| 0.7424 | 0.88 | 11000 | 0.7304 | |
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| 0.7348 | 0.96 | 12000 | 0.7276 | |
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| 0.7421 | 1.04 | 13000 | 0.7327 | |
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| 0.7333 | 1.12 | 14000 | 0.7417 | |
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| 0.7444 | 1.2 | 15000 | 0.7296 | |
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| 0.7463 | 1.28 | 16000 | 0.7257 | |
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| 0.7324 | 1.3600 | 17000 | 0.7253 | |
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| 0.7297 | 1.44 | 18000 | 0.7314 | |
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| 0.7358 | 1.52 | 19000 | 0.7253 | |
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| 0.7442 | 1.6 | 20000 | 0.7248 | |
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| 0.7384 | 1.6800 | 21000 | 0.7388 | |
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| 0.7345 | 1.76 | 22000 | 0.7259 | |
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| 0.7218 | 1.8400 | 23000 | 0.7284 | |
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| 0.7426 | 1.92 | 24000 | 0.7253 | |
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| 0.7375 | 2.0 | 25000 | 0.7389 | |
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| 0.7443 | 2.08 | 26000 | 0.7305 | |
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| 0.7286 | 2.16 | 27000 | 0.7258 | |
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| 0.7269 | 2.24 | 28000 | 0.7264 | |
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| 0.7391 | 2.32 | 29000 | 0.7270 | |
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| 0.7377 | 2.4 | 30000 | 0.7283 | |
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| 0.7319 | 2.48 | 31000 | 0.7329 | |
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| 0.7352 | 2.56 | 32000 | 0.7254 | |
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| 0.7141 | 2.64 | 33000 | 0.7285 | |
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| 0.7317 | 2.7200 | 34000 | 0.7253 | |
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| 0.7334 | 2.8 | 35000 | 0.7305 | |
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| 0.7332 | 2.88 | 36000 | 0.7282 | |
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| 0.7309 | 2.96 | 37000 | 0.7266 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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