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.ipynb_checkpoints/README-checkpoint.md
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---
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license: bigcode-openrail-m
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base_model: bigcode/starcoderbase
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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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model-index:
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- name: output
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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: 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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- name: Accuracy
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type: accuracy
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value: 0.5611769226558302
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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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# output
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This model is a fine-tuned version of [bigcode/starcoderbase](https://huggingface.co/bigcode/starcoderbase) 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: 0.6457
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- Accuracy: 0.5612
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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: 5e-05
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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: 6
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 48
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- total_eval_batch_size: 6
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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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### Training results
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### Framework versions
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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
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