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mt5-summarize-full

Text2Text Generation
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mt5
Generated from Trainer
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Files changed (11) hide show
  1. .gitattributes +1 -0
  2. README.md +74 -0
  3. config.json +36 -0
  4. generation_config.json +10 -0
  5. model.safetensors +3 -0
  6. runs/Jul03_03-52-24_8d438279d74e/events.out.tfevents.1719978766.8d438279d74e.404.0 +3 -0
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  8. spiece.model +3 -0
  9. tokenizer.json +3 -0
  10. tokenizer_config.json +839 -0
  11. training_args.bin +3 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: lunarlist/mt5-summarize
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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: mt5-summarize-full
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+ results: []
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+ ---
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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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+
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+ # mt5-summarize-full
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+
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+ This model is a fine-tuned version of [lunarlist/mt5-summarize](https://huggingface.co/lunarlist/mt5-summarize) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.8640
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+ - Rouge1: 0.3352
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+ - Rouge2: 0.1212
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+ - Rougel: 0.2748
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+ - Rougelsum: 0.4747
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0005
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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: 16
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+ - total_train_batch_size: 32
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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: 90
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | 4.0732 | 1.0667 | 100 | 3.1187 | 0.3331 | 0.1146 | 0.2648 | 0.5137 |
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+ | 3.6546 | 2.1333 | 200 | 2.9872 | 0.3410 | 0.1256 | 0.2894 | 0.4943 |
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+ | 3.3308 | 3.2 | 300 | 2.9373 | 0.3430 | 0.1278 | 0.2881 | 0.4743 |
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+ | 3.276 | 4.2667 | 400 | 2.8782 | 0.3355 | 0.1163 | 0.2793 | 0.4801 |
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+ | 3.1345 | 5.3333 | 500 | 2.9083 | 0.3354 | 0.1216 | 0.2835 | 0.4758 |
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+ | 3.0736 | 6.4 | 600 | 2.8588 | 0.3531 | 0.1353 | 0.2900 | 0.4991 |
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+ | 3.0168 | 7.4667 | 700 | 2.8592 | 0.3436 | 0.1229 | 0.2893 | 0.4863 |
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+ | 2.969 | 8.5333 | 800 | 2.8739 | 0.3528 | 0.1297 | 0.2863 | 0.4968 |
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+ | 2.9677 | 9.6 | 900 | 2.8640 | 0.3352 | 0.1212 | 0.2748 | 0.4747 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.3
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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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