alvarobartt HF staff commited on
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Model save

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Files changed (4) hide show
  1. README.md +7 -7
  2. all_results.json +6 -6
  3. train_results.json +6 -6
  4. trainer_state.json +1925 -707
README.md CHANGED
@@ -1,5 +1,5 @@
1
  ---
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- base_model: google/gemma-2-9b-it
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  datasets:
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  - generator
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  library_name: peft
@@ -9,16 +9,16 @@ tags:
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  - sft
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  - generated_from_trainer
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  model-index:
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- - name: gemma-2-9b-it-lora-magicoder
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  results: []
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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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- # gemma-2-9b-it-lora-magicoder
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- This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on the alvarobartt/Magicoder-OAI dataset.
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  ## Model description
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@@ -42,10 +42,10 @@ The following hyperparameters were used during training:
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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: 4
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  - gradient_accumulation_steps: 2
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- - total_train_batch_size: 32
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- - total_eval_batch_size: 32
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.1
 
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  ---
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+ base_model: google/gemma-2-2b-it
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  datasets:
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  - generator
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  library_name: peft
 
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  - sft
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  - generated_from_trainer
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  model-index:
12
+ - name: gemma-2-2b-it-lora-magicoder
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  results: []
14
  ---
15
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
  should probably proofread and complete it, then remove this comment. -->
18
 
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+ # gemma-2-2b-it-lora-magicoder
20
 
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+ This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) on the generator dataset.
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  ## Model description
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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: 2
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+ - total_train_batch_size: 16
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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: cosine
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  - lr_scheduler_warmup_ratio: 0.1
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