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--- |
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license: apache-2.0 |
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base_model: Salesforce/codegen2-1B |
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tags: |
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- generated_from_trainer |
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datasets: |
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- code_segments_py150k |
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metrics: |
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- accuracy |
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model-index: |
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- name: codegen2-1B_py150_secu |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: code_segments_py150k |
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type: code_segments_py150k |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7620001487509517 |
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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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# codegen2-1B_py150_secu |
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This model is a fine-tuned version of [Salesforce/codegen2-1B](https://huggingface.co/Salesforce/codegen2-1B) on the code_segments_py150k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0928 |
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- Accuracy: 0.7620 |
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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: 1 |
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- eval_batch_size: 8 |
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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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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 16 |
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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: 1.0 |
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### Training results |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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