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  1. .gitattributes +5 -0
  2. README.md +74 -0
  3. all_results.json +22 -0
  4. checkpoint-174018/config.json +59 -0
  5. checkpoint-174018/generation_config.json +12 -0
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  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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  *.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-174018/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+ checkpoint-217522/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+ checkpoint-87009/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: jako_mbartLarge_100p_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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+ # jako_mbartLarge_100p_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: 0.6815
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+ - Bleu: 57.9768
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+ - Gen Len: 17.2796
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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: 500
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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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+ | 0.7241 | 1.0 | 43504 | 0.7178 | 56.112 | 17.3165 |
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+ | 0.5523 | 2.0 | 87009 | 0.6815 | 57.9768 | 17.2796 |
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+ | 0.4356 | 3.0 | 130513 | 0.7014 | 58.5493 | 17.1569 |
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+ | 0.3407 | 4.0 | 174018 | 0.7513 | 58.3826 | 17.1623 |
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+ | 0.2605 | 5.0 | 217522 | 0.8122 | 58.7238 | 17.0888 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
all_results.json ADDED
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+ {
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+ "epoch": 5.0,
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+ "eval_bleu": 57.9768,
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+ "eval_gen_len": 17.2796,
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+ "eval_loss": 0.6814723610877991,
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+ "eval_runtime": 7593.4193,
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+ "eval_samples": 87008,
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+ "eval_samples_per_second": 11.458,
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+ "eval_steps_per_second": 1.432,
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+ "predict_bleu": 58.0783,
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+ "predict_gen_len": 17.2409,
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+ "predict_loss": 0.6792132258415222,
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+ "predict_runtime": 7605.1607,
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+ "predict_samples": 87008,
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+ "predict_samples_per_second": 11.441,
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+ "predict_steps_per_second": 1.43,
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+ "train_loss": 0.5236641572812728,
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+ "train_runtime": 206817.4399,
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+ "train_samples": 696070,
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+ "train_samples_per_second": 50.484,
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+ "train_steps_per_second": 3.155
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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_layerdrop": 0.0,
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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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+ "encoder_attention_heads": 16,
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+ "eos_token_id": 2,
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+ "id2label": {
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+ "0": "LABEL_0",
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