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@@ -4,7 +4,7 @@ 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:
@@ -14,8 +14,8 @@ model-index:
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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
@@ -26,10 +26,10 @@ model-index:
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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/81u023ks)
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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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  tags:
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  - generated_from_trainer
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  datasets:
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+ - andstor/methods2test_small
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  metrics:
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  - accuracy
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  model-index:
 
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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: andstor/methods2test_small fm+fc+c+m+f+t+tc
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+ type: andstor/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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  <!-- 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/andstor/methods2test_small/runs/81u023ks)
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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 andstor/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