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--- |
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base_model: google/pegasus-xsum |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: pegasus-xsum |
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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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# pegasus-xsum |
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This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1676 |
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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: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 2.2677 | 0.4 | 1000 | 0.1598 | |
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| 0.0619 | 0.8 | 2000 | 0.1363 | |
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| 0.0478 | 1.2 | 3000 | 0.1305 | |
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| 0.0421 | 1.6 | 4000 | 0.1298 | |
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| 0.0403 | 2.0 | 5000 | 0.1256 | |
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| 0.0328 | 2.4 | 6000 | 0.1309 | |
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| 0.0314 | 2.8 | 7000 | 0.1296 | |
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| 0.0294 | 3.2 | 8000 | 0.1381 | |
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| 0.0259 | 3.6 | 9000 | 0.1383 | |
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| 0.0251 | 4.0 | 10000 | 0.1380 | |
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| 0.0213 | 4.4 | 11000 | 0.1450 | |
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| 0.0206 | 4.8 | 12000 | 0.1427 | |
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| 0.0201 | 5.2 | 13000 | 0.1520 | |
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| 0.0189 | 5.6 | 14000 | 0.1505 | |
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| 0.0164 | 6.0 | 15000 | 0.1515 | |
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| 0.0153 | 6.4 | 16000 | 0.1594 | |
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| 0.0153 | 6.8 | 17000 | 0.1570 | |
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| 0.0149 | 7.2 | 18000 | 0.1652 | |
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| 0.0136 | 7.6 | 19000 | 0.1662 | |
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| 0.013 | 8.0 | 20000 | 0.1676 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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