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  2. adapter_config.json +5 -5
  3. adapter_model.bin +1 -1
  4. checkpoint-1446/adapter_model.safetensors +0 -3
  5. checkpoint-1446/optimizer.pt +0 -3
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  9. {checkpoint-723 β†’ checkpoint-362}/adapter_model.safetensors +1 -1
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  24. {checkpoint-1446 β†’ checkpoint-362}/training_args.bin +1 -1
  25. checkpoint-723/README.md +0 -202
  26. checkpoint-723/adapter_config.json +0 -34
  27. checkpoint-723/rng_state_1.pth +0 -3
  28. checkpoint-723/scheduler.pt +0 -3
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  31. checkpoint-723/tokenizer_config.json +0 -2064
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94
  This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct) on the None dataset.
95
  It achieves the following results on the evaluation set:
96
- - Loss: 1.2243
97
 
98
  ## Model description
99
 
@@ -117,26 +117,22 @@ The following hyperparameters were used during training:
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128
  ### Training results
129
 
130
  | Training Loss | Epoch | Step | Validation Loss |
131
  |:-------------:|:------:|:----:|:---------------:|
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- | 1.8618 | 0.0014 | 1 | 1.4421 |
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141
 
142
  ### Framework versions
 
60
 
61
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  micro_batch_size: 4
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+ num_epochs: 1
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  optimizer: adamw_hf
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93
 
94
  This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct) on the None dataset.
95
  It achieves the following results on the evaluation set:
96
+ - Loss: 1.0862
97
 
98
  ## Model description
99
 
 
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128
  ### Training results
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130
  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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- ---
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- base_model: unsloth/Meta-Llama-3.1-8B-Instruct
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- library_name: peft
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- ---
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- # Model Card for Model ID
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- ## Model Details
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- ### Model Description
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- - **Developed by:** [More Information Needed]
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- ## Uses
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- ## How to Get Started with the Model
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- ## Training Details
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- [More Information Needed]
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- [More Information Needed]
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- ## Environmental Impact
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- [More Information Needed]
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- ### Compute Infrastructure
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- [More Information Needed]
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- #### Hardware
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- [More Information Needed]
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- #### Software
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- [More Information Needed]
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- ## Citation [optional]
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- **BibTeX:**
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- **APA:**
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- ## Glossary [optional]
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- [More Information Needed]
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- ## More Information [optional]
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- [More Information Needed]
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- ## Model Card Authors [optional]
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- [More Information Needed]
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- ## Model Card Contact
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- ### Framework versions
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- - PEFT 0.12.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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