Model save
Browse files- README.md +58 -0
- generation_config.json +8 -0
- logs/events.out.tfevents.1739384784.tacosec0.1044786.0 +2 -2
- model.safetensors +1 -1
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: Salesforce/codet5-base
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tags:
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- generated_from_trainer
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model-index:
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- name: py311-pylingual-v1-statement
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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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should probably proofread and complete it, then remove this comment. -->
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# py311-pylingual-v1-statement
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This model is a fine-tuned version of [Salesforce/codet5-base](https://huggingface.co/Salesforce/codet5-base) on an unknown dataset.
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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: 24
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- eval_batch_size: 24
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- total_train_batch_size: 48
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- total_eval_batch_size: 48
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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: 2
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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 4.48.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.21.0
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"decoder_start_token_id": 0,
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"eos_token_id": 2,
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"pad_token_id": 0,
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"transformers_version": "4.48.2"
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}
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logs/events.out.tfevents.1739384784.tacosec0.1044786.0
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model.safetensors
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