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--- |
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base_model: google/pegasus-x-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: google/pegasus-x-base |
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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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# google/pegasus-x-base |
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This model is a fine-tuned version of [google/pegasus-x-base](https://huggingface.co/google/pegasus-x-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0135 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 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 | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 8.9092 | 0.1008 | 10 | 8.5348 | |
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| 7.9162 | 0.2015 | 20 | 7.5592 | |
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| 7.3907 | 0.3023 | 30 | 6.9080 | |
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| 6.8587 | 0.4030 | 40 | 6.1464 | |
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| 5.7817 | 0.5038 | 50 | 5.2883 | |
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| 5.0792 | 0.6045 | 60 | 3.9477 | |
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| 4.1259 | 0.7053 | 70 | 2.7538 | |
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| 3.0821 | 0.8060 | 80 | 1.7983 | |
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| 2.2714 | 0.9068 | 90 | 1.4814 | |
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| 1.7994 | 1.0076 | 100 | 1.4092 | |
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| 1.4936 | 1.1083 | 110 | 1.3189 | |
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| 1.6535 | 1.2091 | 120 | 1.2445 | |
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| 1.3122 | 1.3098 | 130 | 1.2139 | |
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| 1.0667 | 1.4106 | 140 | 1.1800 | |
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| 1.274 | 1.5113 | 150 | 1.1507 | |
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| 1.1739 | 1.6121 | 160 | 1.1279 | |
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| 1.1871 | 1.7128 | 170 | 1.1094 | |
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| 1.2037 | 1.8136 | 180 | 1.0973 | |
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| 1.0839 | 1.9144 | 190 | 1.0832 | |
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| 1.0738 | 2.0151 | 200 | 1.0752 | |
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| 1.0955 | 2.1159 | 210 | 1.0695 | |
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| 1.1285 | 2.2166 | 220 | 1.0629 | |
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| 0.9973 | 2.3174 | 230 | 1.0574 | |
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| 1.0522 | 2.4181 | 240 | 1.0557 | |
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| 1.0803 | 2.5189 | 250 | 1.0458 | |
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| 1.0707 | 2.6196 | 260 | 1.0425 | |
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| 1.1868 | 2.7204 | 270 | 1.0384 | |
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| 1.0117 | 2.8212 | 280 | 1.0374 | |
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| 0.9206 | 2.9219 | 290 | 1.0347 | |
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| 1.0099 | 3.0227 | 300 | 1.0306 | |
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| 1.0459 | 3.1234 | 310 | 1.0307 | |
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| 1.0721 | 3.2242 | 320 | 1.0313 | |
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| 1.015 | 3.3249 | 330 | 1.0278 | |
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| 1.0358 | 3.4257 | 340 | 1.0237 | |
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| 0.9608 | 3.5264 | 350 | 1.0206 | |
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| 1.0416 | 3.6272 | 360 | 1.0202 | |
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| 0.9304 | 3.7280 | 370 | 1.0201 | |
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| 1.0447 | 3.8287 | 380 | 1.0187 | |
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| 1.0007 | 3.9295 | 390 | 1.0180 | |
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| 1.1681 | 4.0302 | 400 | 1.0168 | |
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| 1.0258 | 4.1310 | 410 | 1.0163 | |
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| 1.1054 | 4.2317 | 420 | 1.0153 | |
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| 0.907 | 4.3325 | 430 | 1.0154 | |
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| 0.935 | 4.4332 | 440 | 1.0151 | |
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| 0.9904 | 4.5340 | 450 | 1.0145 | |
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| 0.9735 | 4.6348 | 460 | 1.0142 | |
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| 0.9633 | 4.7355 | 470 | 1.0138 | |
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| 1.2809 | 4.8363 | 480 | 1.0136 | |
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| 1.0361 | 4.9370 | 490 | 1.0135 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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