Tongyan Bai commited on
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https://huggingface.co./tongyanb/lab2_adam

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Files changed (5) hide show
  1. README.md +13 -28
  2. config.json +1 -1
  3. generation_config.json +1 -1
  4. model.safetensors +1 -1
  5. training_args.bin +1 -1
README.md CHANGED
@@ -5,24 +5,9 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - kde4
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- metrics:
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- - bleu
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  model-index:
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  - name: marian-finetuned-kde4-en-to-fr
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- results:
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- - task:
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- name: Sequence-to-sequence Language Modeling
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- type: text2text-generation
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- dataset:
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- name: kde4
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- type: kde4
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- config: en-fr
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- split: train
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- args: en-fr
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- metrics:
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- - name: Bleu
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- type: bleu
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- value: 52.60158308795034
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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
@@ -32,8 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki-NLP/opus-mt-en-fr) on the kde4 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8607
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- - Bleu: 52.6016
 
 
 
 
 
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  ## Model description
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@@ -53,24 +43,19 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 32
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  - eval_batch_size: 64
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  - seed: 42
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- - gradient_accumulation_steps: 4
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  - total_train_batch_size: 128
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 2
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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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-
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  ### Framework versions
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- - Transformers 4.38.1
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- - Pytorch 2.1.0+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  - generated_from_trainer
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  datasets:
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  - kde4
 
 
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  model-index:
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  - name: marian-finetuned-kde4-en-to-fr
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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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  This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki-NLP/opus-mt-en-fr) on the kde4 dataset.
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  It achieves the following results on the evaluation set:
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+ - eval_loss: 0.9633
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+ - eval_bleu: 49.9655
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+ - eval_runtime: 162.904
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+ - eval_samples_per_second: 12.903
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+ - eval_steps_per_second: 0.203
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+ - epoch: 0.0
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+ - step: 4
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 64
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  - eval_batch_size: 64
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  - seed: 42
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+ - gradient_accumulation_steps: 2
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  - total_train_batch_size: 128
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 1
 
 
 
 
 
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  ### Framework versions
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
config.json CHANGED
@@ -56,7 +56,7 @@
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  "share_encoder_decoder_embeddings": true,
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  "static_position_embeddings": true,
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  "torch_dtype": "float32",
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- "transformers_version": "4.38.1",
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  "use_cache": true,
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  "vocab_size": 59514
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  }
 
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  "share_encoder_decoder_embeddings": true,
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  "static_position_embeddings": true,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.38.2",
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  "use_cache": true,
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  "vocab_size": 59514
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  }
generation_config.json CHANGED
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- "transformers_version": "4.38.1"
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  }
 
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  "num_beams": 4,
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  "pad_token_id": 59513,
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  "renormalize_logits": true,
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+ "transformers_version": "4.38.2"
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  }
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