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yesj1234
/
koja_mbartLarge_reverse13p_run1

Text2Text Generation
Transformers
PyTorch
Korean
Japanese
mbart
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. .gitattributes +3 -0
  2. README.md +75 -0
  3. all_results.json +22 -0
  4. checkpoint-3200/config.json +59 -0
  5. checkpoint-3200/generation_config.json +12 -0
  6. checkpoint-3200/optimizer.pt +3 -0
  7. checkpoint-3200/pytorch_model.bin +3 -0
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  9. checkpoint-3200/rng_state_1.pth +3 -0
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  34. config.json +59 -0
  35. eval_results.json +10 -0
  36. generated_predictions.txt +0 -0
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  38. predict_results.json +9 -0
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.gitattributes CHANGED
@@ -33,3 +33,6 @@ 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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README.md ADDED
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+ ---
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+ language:
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+ - ko
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+ - ja
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+ base_model: facebook/mbart-large-50-many-to-many-mmt
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - bleu
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+ model-index:
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+ - name: koja_reverse_13p_run1
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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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+ # koja_reverse_13p_run1
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+
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+ This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3532
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+ - Bleu: 5.7574
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+ - Gen Len: 20.4109
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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: 5e-05
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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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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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+ - total_eval_batch_size: 16
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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: 200
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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 | Bleu | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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+ | 1.9693 | 0.42 | 800 | 1.5445 | 4.3096 | 20.2019 |
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+ | 1.4914 | 0.83 | 1600 | 1.4233 | 4.307 | 20.1204 |
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+ | 1.4272 | 1.25 | 2400 | 1.3761 | 4.8111 | 22.8555 |
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+ | 1.1571 | 1.66 | 3200 | 1.3532 | 5.7574 | 21.151 |
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+ | 1.0833 | 2.08 | 4000 | 1.3449 | 5.652 | 21.2158 |
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+ | 0.9394 | 2.49 | 4800 | 1.3905 | 5.45 | 19.9005 |
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+ | 0.8633 | 2.91 | 5600 | 1.3719 | 4.9973 | 19.7844 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ {
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+ "epoch": 2.91,
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+ "eval_loss": 1.3532484769821167,
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+ "eval_samples_per_second": 12.927,
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+ "eval_steps_per_second": 0.809,
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+ "predict_bleu": 4.2372,
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+ "predict_loss": 1.3588087558746338,
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+ "predict_samples_per_second": 12.673,
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+ "predict_steps_per_second": 0.793,
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+ "train_loss": 1.2439973626817975,
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+ "train_runtime": 14074.9837,
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+ "train_samples": 61615,
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+ "train_samples_per_second": 43.776,
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+ "train_steps_per_second": 1.368
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+ }
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