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README.md CHANGED
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- license: mit
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ base_model: Salesforce/codet5-small
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+ model-index:
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+ - name: codeT5-small-context
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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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+ # codeT5-small-context
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+
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+ This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8472
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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: 0.0001
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+ - train_batch_size: 12
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+ - eval_batch_size: 8
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+ - seed: 42
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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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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 1.1783 | 1.0 | 4383 | 0.9338 |
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+ | 1.0719 | 2.0 | 8766 | 0.8854 |
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+ | 1.0357 | 3.0 | 13149 | 0.8605 |
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+ | 1.0336 | 4.0 | 17532 | 0.8515 |
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+ | 0.9942 | 5.0 | 21915 | 0.8472 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.10.0
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.1+cu121
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+ - Tokenizers 0.19.1
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+ {
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+ "alpha_pattern": {},
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+ "base_model_class": "T5ForConditionalGeneration",
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+ "parent_library": "transformers.models.t5.modeling_t5"
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+ },
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+ "base_model_name_or_path": "Salesforce/codet5-small",
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+ "bias": "none",
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+ "inference_mode": true,
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+ "megatron_core": "megatron.core",
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+ "v",
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+ "q"
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+ ],
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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