iSathyam03
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Training complete
Browse files- README.md +76 -0
- generation_config.json +16 -0
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: Helsinki-NLP/opus-mt-en-jap
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tags:
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- translation
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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: sattu-finetuned-kde4-en-to-jap
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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-ja
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split: train
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args: en-ja
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metrics:
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- name: Bleu
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type: bleu
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value: 20.727494887708588
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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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# sattu-finetuned-kde4-en-to-jap
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-jap](https://huggingface.co/Helsinki-NLP/opus-mt-en-jap) on the kde4 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4199
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- Model Preparation Time: 0.0018
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- Bleu: 20.7275
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 8
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 3
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.47.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.21.0
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generation_config.json
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{
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"bad_words_ids": [
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[
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46275
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]
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],
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"bos_token_id": 0,
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"decoder_start_token_id": 46275,
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"eos_token_id": 0,
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"forced_eos_token_id": 0,
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"max_length": 512,
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"num_beams": 4,
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"pad_token_id": 46275,
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"renormalize_logits": true,
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"transformers_version": "4.47.0"
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}
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