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--- |
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license: bsd-3-clause |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fals3/methods2test_small |
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metrics: |
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- accuracy |
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base_model: Salesforce/codegen-350M-multi |
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model-index: |
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- name: output |
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results: |
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- task: |
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type: text-generation |
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name: Causal Language Modeling |
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dataset: |
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name: fals3/methods2test_small fm+fc+c+m+f+t+tc |
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type: fals3/methods2test_small |
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args: fm+fc+c+m+f+t+tc |
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metrics: |
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- type: accuracy |
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value: 0.6807527762973363 |
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name: Accuracy |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/fals3/methods2test_small/runs/entir0q9) |
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# output |
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This model is a fine-tuned version of [Salesforce/codegen-350M-multi](https://huggingface.co/Salesforce/codegen-350M-multi) on the fals3/methods2test_small fm+fc+c+m+f+t+tc dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7674 |
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- Accuracy: 0.6808 |
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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: 0.0003 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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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: 8 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 2 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3.0 |
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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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- PEFT 0.10.0 |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.1 |
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- Tokenizers 0.19.1 |
