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  1. .gitattributes +5 -0
  2. README.md +75 -0
  3. all_results.json +22 -0
  4. checkpoint-129072/config.json +59 -0
  5. checkpoint-129072/generation_config.json +12 -0
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  49. config.json +59 -0
  50. eval_results.json +10 -0
.gitattributes CHANGED
@@ -33,3 +33,8 @@ 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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+ checkpoint-215120/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+ checkpoint-258144/tokenizer.json 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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+ - ja
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+ - ko
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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: finetuned_model
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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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+ # finetuned_model
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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: 0.6568
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+ - Bleu: 58.837
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+ - Gen Len: 15.7689
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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: 2
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+ - eval_batch_size: 2
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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: 16
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+ - total_eval_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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+ - lr_scheduler_warmup_steps: 2500
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+ - num_epochs: 15
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+ - mixed_precision_training: Native AMP
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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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+ | 0.7629 | 1.0 | 43024 | 0.7231 | 54.9608 | 16.1273 |
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+ | 0.6355 | 2.0 | 86048 | 0.6641 | 57.5735 | 15.9938 |
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+ | 0.5464 | 3.0 | 129072 | 0.6568 | 58.837 | 15.7689 |
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+ | 0.4444 | 4.0 | 172096 | 0.6777 | 59.3055 | 15.7545 |
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+ | 0.3458 | 5.0 | 215120 | 0.7215 | 59.1341 | 15.7016 |
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+ | 0.2702 | 6.0 | 258144 | 0.8013 | 59.0721 | 15.6936 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
all_results.json ADDED
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+ {
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+ "epoch": 6.0,
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+ "eval_bleu": 58.837,
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+ "eval_gen_len": 15.7689,
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+ "eval_loss": 0.6568061113357544,
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+ "eval_runtime": 6763.7413,
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+ "eval_samples": 85914,
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+ "eval_samples_per_second": 12.702,
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+ "eval_steps_per_second": 1.588,
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+ "predict_bleu": 59.427,
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+ "predict_gen_len": 16.2418,
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+ "predict_loss": 0.6393086910247803,
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+ "predict_runtime": 7570.8911,
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+ "predict_samples": 94835,
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+ "predict_samples_per_second": 12.526,
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+ "predict_steps_per_second": 1.566,
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+ "train_loss": 0.5181208364993382,
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+ "train_runtime": 241803.971,
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+ "train_samples": 688378,
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+ "train_samples_per_second": 42.703,
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+ "train_steps_per_second": 2.669
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+ }
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+ "activation_function": "relu",
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+ "MBartForConditionalGeneration"
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+ "decoder_attention_heads": 16,
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+ "decoder_ffn_dim": 4096,
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+ "decoder_layers": 12,
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+ "decoder_start_token_id": 2,
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+ "dropout": 0.1,
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+ "early_stopping": true,
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+ "vocab_size": 250054
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+ }
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