update qlora
Browse files- README.md +418 -2
- adapter_config.json +9 -2
- adapter_model.bin +2 -2
- training_log.json +0 -16
- training_parameters.json +19 -12
- training_prompt.json +3 -1
README.md
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@@ -1,10 +1,342 @@
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---
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library_name: peft
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---
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| 4 |
## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: True
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- load_in_4bit: False
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- llm_int8_threshold: 6.0
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: True
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- load_in_4bit: False
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- llm_int8_threshold: 6.0
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- bnb_4bit_quant_type: fp4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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| 28 |
### Framework versions
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| 29 |
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-
- PEFT 0.5.0.dev0
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| 31 |
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-
- PEFT 0.
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| 1 |
---
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library_name: peft
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+
base_model: models\LLaMA2-13B-Tiefighter
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| 4 |
---
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| 5 |
+
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| 6 |
+
# Model Card for Model ID
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| 7 |
+
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| 8 |
+
<!-- Provide a quick summary of what the model is/does. -->
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| 9 |
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| 10 |
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| 11 |
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## Model Details
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| 13 |
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| 14 |
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### Model Description
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| 15 |
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| 16 |
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<!-- Provide a longer summary of what this model is. -->
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| 17 |
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| 18 |
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| 19 |
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| 20 |
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- **Developed by:** [More Information Needed]
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| 21 |
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- **Funded by [optional]:** [More Information Needed]
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| 22 |
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- **Shared by [optional]:** [More Information Needed]
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| 23 |
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- **Model type:** [More Information Needed]
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| 24 |
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- **Language(s) (NLP):** [More Information Needed]
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| 25 |
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- **License:** [More Information Needed]
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| 26 |
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- **Finetuned from model [optional]:** [More Information Needed]
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| 27 |
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| 28 |
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### Model Sources [optional]
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| 29 |
+
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| 30 |
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<!-- Provide the basic links for the model. -->
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| 31 |
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| 32 |
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- **Repository:** [More Information Needed]
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| 33 |
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- **Paper [optional]:** [More Information Needed]
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| 34 |
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- **Demo [optional]:** [More Information Needed]
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| 35 |
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| 36 |
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## Uses
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| 37 |
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| 38 |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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| 39 |
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| 40 |
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### Direct Use
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| 41 |
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| 42 |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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| 43 |
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| 44 |
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[More Information Needed]
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| 45 |
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| 46 |
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### Downstream Use [optional]
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| 47 |
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| 48 |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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| 49 |
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| 50 |
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[More Information Needed]
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| 51 |
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| 52 |
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### Out-of-Scope Use
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| 53 |
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| 54 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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| 55 |
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| 56 |
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[More Information Needed]
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| 57 |
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| 58 |
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## Bias, Risks, and Limitations
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| 59 |
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| 60 |
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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| 61 |
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| 62 |
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[More Information Needed]
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| 63 |
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| 64 |
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### Recommendations
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| 65 |
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| 66 |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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| 67 |
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| 68 |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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| 69 |
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| 70 |
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## How to Get Started with the Model
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| 71 |
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| 72 |
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Use the code below to get started with the model.
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| 73 |
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| 74 |
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[More Information Needed]
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| 75 |
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| 76 |
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## Training Details
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| 77 |
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| 78 |
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### Training Data
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| 79 |
+
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| 80 |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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| 81 |
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| 82 |
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[More Information Needed]
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| 83 |
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| 84 |
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### Training Procedure
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| 85 |
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| 86 |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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| 87 |
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| 88 |
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#### Preprocessing [optional]
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| 89 |
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| 90 |
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[More Information Needed]
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| 91 |
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| 92 |
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| 93 |
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#### Training Hyperparameters
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| 94 |
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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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| 98 |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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| 100 |
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| 101 |
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[More Information Needed]
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| 102 |
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| 103 |
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## Evaluation
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| 104 |
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| 105 |
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<!-- This section describes the evaluation protocols and provides the results. -->
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| 106 |
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| 107 |
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### Testing Data, Factors & Metrics
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| 108 |
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| 109 |
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#### Testing Data
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| 110 |
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| 111 |
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<!-- This should link to a Dataset Card if possible. -->
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| 112 |
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| 113 |
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[More Information Needed]
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| 114 |
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| 115 |
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#### Factors
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| 116 |
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| 117 |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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| 118 |
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| 119 |
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[More Information Needed]
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| 120 |
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| 121 |
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#### Metrics
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| 122 |
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| 123 |
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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| 124 |
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| 125 |
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[More Information Needed]
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| 126 |
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| 127 |
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### Results
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| 128 |
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| 129 |
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[More Information Needed]
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| 130 |
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| 131 |
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#### Summary
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| 132 |
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| 133 |
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| 134 |
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## Model Examination [optional]
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| 136 |
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| 137 |
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<!-- Relevant interpretability work for the model goes here -->
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| 138 |
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| 139 |
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[More Information Needed]
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| 140 |
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| 141 |
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## Environmental Impact
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| 142 |
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| 143 |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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| 144 |
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| 145 |
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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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| 146 |
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| 147 |
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- **Hardware Type:** [More Information Needed]
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| 148 |
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- **Hours used:** [More Information Needed]
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| 149 |
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- **Cloud Provider:** [More Information Needed]
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| 150 |
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- **Compute Region:** [More Information Needed]
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| 151 |
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- **Carbon Emitted:** [More Information Needed]
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| 152 |
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| 153 |
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## Technical Specifications [optional]
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| 154 |
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| 155 |
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### Model Architecture and Objective
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| 156 |
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| 157 |
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[More Information Needed]
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| 158 |
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| 159 |
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### Compute Infrastructure
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| 160 |
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| 161 |
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[More Information Needed]
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| 162 |
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| 163 |
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#### Hardware
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| 164 |
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| 165 |
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[More Information Needed]
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| 166 |
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| 167 |
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#### Software
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| 168 |
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| 169 |
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[More Information Needed]
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| 170 |
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| 171 |
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## Citation [optional]
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| 172 |
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| 173 |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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| 174 |
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**BibTeX:**
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| 176 |
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[More Information Needed]
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**APA:**
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| 180 |
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| 181 |
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[More Information Needed]
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| 182 |
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| 183 |
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## Glossary [optional]
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| 184 |
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| 185 |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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| 186 |
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| 187 |
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[More Information Needed]
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| 188 |
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## More Information [optional]
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| 190 |
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| 191 |
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[More Information Needed]
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| 192 |
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## Model Card Authors [optional]
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| 194 |
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[More Information Needed]
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## Model Card Contact
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| 198 |
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| 199 |
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[More Information Needed]
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| 200 |
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## Training procedure
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| 203 |
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: QuantizationMethod.BITS_AND_BYTES
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: False
|
| 215 |
+
- bnb_4bit_compute_dtype: float16
|
| 216 |
+
|
| 217 |
+
### Framework versions
|
| 218 |
+
|
| 219 |
+
|
| 220 |
+
- PEFT 0.6.2
|
| 221 |
+
## Training procedure
|
| 222 |
+
|
| 223 |
+
|
| 224 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 225 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 226 |
+
- load_in_8bit: False
|
| 227 |
+
- load_in_4bit: True
|
| 228 |
+
- llm_int8_threshold: 6.0
|
| 229 |
+
- llm_int8_skip_modules: None
|
| 230 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
| 231 |
+
- llm_int8_has_fp16_weight: False
|
| 232 |
+
- bnb_4bit_quant_type: nf4
|
| 233 |
+
- bnb_4bit_use_double_quant: False
|
| 234 |
+
- bnb_4bit_compute_dtype: float16
|
| 235 |
+
|
| 236 |
+
### Framework versions
|
| 237 |
+
|
| 238 |
+
|
| 239 |
+
- PEFT 0.6.2
|
| 240 |
+
## Training procedure
|
| 241 |
+
|
| 242 |
+
|
| 243 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 244 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 245 |
+
- load_in_8bit: False
|
| 246 |
+
- load_in_4bit: True
|
| 247 |
+
- llm_int8_threshold: 6.0
|
| 248 |
+
- llm_int8_skip_modules: None
|
| 249 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
| 250 |
+
- llm_int8_has_fp16_weight: False
|
| 251 |
+
- bnb_4bit_quant_type: nf4
|
| 252 |
+
- bnb_4bit_use_double_quant: False
|
| 253 |
+
- bnb_4bit_compute_dtype: float16
|
| 254 |
+
|
| 255 |
+
### Framework versions
|
| 256 |
+
|
| 257 |
+
|
| 258 |
+
- PEFT 0.6.2
|
| 259 |
+
## Training procedure
|
| 260 |
+
|
| 261 |
+
|
| 262 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 263 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 264 |
+
- load_in_8bit: False
|
| 265 |
+
- load_in_4bit: True
|
| 266 |
+
- llm_int8_threshold: 6.0
|
| 267 |
+
- llm_int8_skip_modules: None
|
| 268 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
| 269 |
+
- llm_int8_has_fp16_weight: False
|
| 270 |
+
- bnb_4bit_quant_type: nf4
|
| 271 |
+
- bnb_4bit_use_double_quant: False
|
| 272 |
+
- bnb_4bit_compute_dtype: float16
|
| 273 |
+
|
| 274 |
+
### Framework versions
|
| 275 |
+
|
| 276 |
+
|
| 277 |
+
- PEFT 0.6.2
|
| 278 |
## Training procedure
|
| 279 |
|
| 280 |
|
| 281 |
The following `bitsandbytes` quantization config was used during training:
|
| 282 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 283 |
+
- load_in_8bit: False
|
| 284 |
+
- load_in_4bit: True
|
| 285 |
+
- llm_int8_threshold: 6.0
|
| 286 |
+
- llm_int8_skip_modules: None
|
| 287 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
| 288 |
+
- llm_int8_has_fp16_weight: False
|
| 289 |
+
- bnb_4bit_quant_type: nf4
|
| 290 |
+
- bnb_4bit_use_double_quant: False
|
| 291 |
+
- bnb_4bit_compute_dtype: float16
|
| 292 |
+
|
| 293 |
+
### Framework versions
|
| 294 |
+
|
| 295 |
+
|
| 296 |
+
- PEFT 0.6.2
|
| 297 |
+
## Training procedure
|
| 298 |
+
|
| 299 |
+
|
| 300 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 301 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 302 |
+
- load_in_8bit: False
|
| 303 |
+
- load_in_4bit: True
|
| 304 |
+
- llm_int8_threshold: 6.0
|
| 305 |
+
- llm_int8_skip_modules: None
|
| 306 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
| 307 |
+
- llm_int8_has_fp16_weight: False
|
| 308 |
+
- bnb_4bit_quant_type: nf4
|
| 309 |
+
- bnb_4bit_use_double_quant: False
|
| 310 |
+
- bnb_4bit_compute_dtype: float16
|
| 311 |
+
|
| 312 |
+
### Framework versions
|
| 313 |
+
|
| 314 |
+
|
| 315 |
+
- PEFT 0.6.2
|
| 316 |
+
## Training procedure
|
| 317 |
+
|
| 318 |
+
|
| 319 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 320 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 321 |
+
- load_in_8bit: True
|
| 322 |
+
- load_in_4bit: False
|
| 323 |
+
- llm_int8_threshold: 6.0
|
| 324 |
+
- llm_int8_skip_modules: None
|
| 325 |
+
- llm_int8_enable_fp32_cpu_offload: True
|
| 326 |
+
- llm_int8_has_fp16_weight: False
|
| 327 |
+
- bnb_4bit_quant_type: fp4
|
| 328 |
+
- bnb_4bit_use_double_quant: False
|
| 329 |
+
- bnb_4bit_compute_dtype: float32
|
| 330 |
+
|
| 331 |
+
### Framework versions
|
| 332 |
+
|
| 333 |
+
|
| 334 |
+
- PEFT 0.6.2
|
| 335 |
+
## Training procedure
|
| 336 |
+
|
| 337 |
+
|
| 338 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 339 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 340 |
- load_in_8bit: True
|
| 341 |
- load_in_4bit: False
|
| 342 |
- llm_int8_threshold: 6.0
|
|
|
|
| 347 |
- bnb_4bit_use_double_quant: False
|
| 348 |
- bnb_4bit_compute_dtype: float32
|
| 349 |
|
| 350 |
+
### Framework versions
|
| 351 |
+
|
| 352 |
+
|
| 353 |
+
- PEFT 0.6.2
|
| 354 |
+
## Training procedure
|
| 355 |
+
|
| 356 |
+
|
| 357 |
The following `bitsandbytes` quantization config was used during training:
|
| 358 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 359 |
- load_in_8bit: True
|
| 360 |
- load_in_4bit: False
|
| 361 |
- llm_int8_threshold: 6.0
|
|
|
|
| 365 |
- bnb_4bit_quant_type: fp4
|
| 366 |
- bnb_4bit_use_double_quant: False
|
| 367 |
- bnb_4bit_compute_dtype: float32
|
| 368 |
+
|
| 369 |
+
### Framework versions
|
| 370 |
+
|
| 371 |
+
|
| 372 |
+
- PEFT 0.6.2
|
| 373 |
+
## Training procedure
|
| 374 |
+
|
| 375 |
+
|
| 376 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 377 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 378 |
+
- load_in_8bit: False
|
| 379 |
+
- load_in_4bit: True
|
| 380 |
+
- llm_int8_threshold: 6.0
|
| 381 |
+
- llm_int8_skip_modules: None
|
| 382 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
| 383 |
+
- llm_int8_has_fp16_weight: False
|
| 384 |
+
- bnb_4bit_quant_type: nf4
|
| 385 |
+
- bnb_4bit_use_double_quant: False
|
| 386 |
+
- bnb_4bit_compute_dtype: float16
|
| 387 |
+
|
| 388 |
+
### Framework versions
|
| 389 |
+
|
| 390 |
+
|
| 391 |
+
- PEFT 0.6.2
|
| 392 |
+
## Training procedure
|
| 393 |
+
|
| 394 |
+
|
| 395 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 396 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 397 |
+
- load_in_8bit: False
|
| 398 |
+
- load_in_4bit: True
|
| 399 |
+
- llm_int8_threshold: 6.0
|
| 400 |
+
- llm_int8_skip_modules: None
|
| 401 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
| 402 |
+
- llm_int8_has_fp16_weight: False
|
| 403 |
+
- bnb_4bit_quant_type: nf4
|
| 404 |
+
- bnb_4bit_use_double_quant: False
|
| 405 |
+
- bnb_4bit_compute_dtype: float16
|
| 406 |
+
|
| 407 |
+
### Framework versions
|
| 408 |
+
|
| 409 |
+
|
| 410 |
+
- PEFT 0.6.2
|
| 411 |
+
## Training procedure
|
| 412 |
+
|
| 413 |
+
|
| 414 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 415 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 416 |
+
- load_in_8bit: False
|
| 417 |
+
- load_in_4bit: True
|
| 418 |
+
- llm_int8_threshold: 6.0
|
| 419 |
+
- llm_int8_skip_modules: None
|
| 420 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
| 421 |
+
- llm_int8_has_fp16_weight: False
|
| 422 |
+
- bnb_4bit_quant_type: nf4
|
| 423 |
+
- bnb_4bit_use_double_quant: False
|
| 424 |
+
- bnb_4bit_compute_dtype: float16
|
| 425 |
+
|
| 426 |
+
### Framework versions
|
| 427 |
+
|
| 428 |
+
|
| 429 |
+
- PEFT 0.6.2
|
| 430 |
+
## Training procedure
|
| 431 |
+
|
| 432 |
+
|
| 433 |
+
The following `bitsandbytes` quantization config was used during training:
|
| 434 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
| 435 |
+
- load_in_8bit: False
|
| 436 |
+
- load_in_4bit: True
|
| 437 |
+
- llm_int8_threshold: 6.0
|
| 438 |
+
- llm_int8_skip_modules: None
|
| 439 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
| 440 |
+
- llm_int8_has_fp16_weight: False
|
| 441 |
+
- bnb_4bit_quant_type: nf4
|
| 442 |
+
- bnb_4bit_use_double_quant: False
|
| 443 |
+
- bnb_4bit_compute_dtype: float16
|
| 444 |
+
|
| 445 |
### Framework versions
|
| 446 |
|
|
|
|
| 447 |
|
| 448 |
+
- PEFT 0.6.2
|
adapter_config.json
CHANGED
|
@@ -1,6 +1,7 @@
|
|
| 1 |
{
|
|
|
|
| 2 |
"auto_mapping": null,
|
| 3 |
-
"base_model_name_or_path": "models
|
| 4 |
"bias": "none",
|
| 5 |
"fan_in_fan_out": false,
|
| 6 |
"inference_mode": true,
|
|
@@ -12,10 +13,16 @@
|
|
| 12 |
"modules_to_save": null,
|
| 13 |
"peft_type": "LORA",
|
| 14 |
"r": 128,
|
|
|
|
| 15 |
"revision": null,
|
| 16 |
"target_modules": [
|
|
|
|
|
|
|
|
|
|
| 17 |
"q_proj",
|
| 18 |
-
"
|
|
|
|
|
|
|
| 19 |
],
|
| 20 |
"task_type": "CAUSAL_LM"
|
| 21 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"alpha_pattern": {},
|
| 3 |
"auto_mapping": null,
|
| 4 |
+
"base_model_name_or_path": "models\\LLaMA2-13B-Tiefighter",
|
| 5 |
"bias": "none",
|
| 6 |
"fan_in_fan_out": false,
|
| 7 |
"inference_mode": true,
|
|
|
|
| 13 |
"modules_to_save": null,
|
| 14 |
"peft_type": "LORA",
|
| 15 |
"r": 128,
|
| 16 |
+
"rank_pattern": {},
|
| 17 |
"revision": null,
|
| 18 |
"target_modules": [
|
| 19 |
+
"gate_proj",
|
| 20 |
+
"o_proj",
|
| 21 |
+
"down_proj",
|
| 22 |
"q_proj",
|
| 23 |
+
"up_proj",
|
| 24 |
+
"v_proj",
|
| 25 |
+
"k_proj"
|
| 26 |
],
|
| 27 |
"task_type": "CAUSAL_LM"
|
| 28 |
}
|
adapter_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a28bb35807a1e0701ca619f722aba6f153335a231ca8fb59ee8c3af441f4bf98
|
| 3 |
+
size 2002982666
|
training_log.json
DELETED
|
@@ -1,16 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"base_model_name": "mythalion-13b",
|
| 3 |
-
"base_model_class": "LlamaForCausalLM",
|
| 4 |
-
"base_loaded_in_4bit": false,
|
| 5 |
-
"base_loaded_in_8bit": true,
|
| 6 |
-
"projections": "q, v",
|
| 7 |
-
"loss": 0.9646,
|
| 8 |
-
"learning_rate": 0.00015,
|
| 9 |
-
"epoch": 1.88,
|
| 10 |
-
"current_steps": 46,
|
| 11 |
-
"train_runtime": 87.3735,
|
| 12 |
-
"train_samples_per_second": 2.232,
|
| 13 |
-
"train_steps_per_second": 0.034,
|
| 14 |
-
"total_flos": 2487721328640000.0,
|
| 15 |
-
"train_loss": 0.9646244049072266
|
| 16 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
training_parameters.json
CHANGED
|
@@ -1,30 +1,37 @@
|
|
| 1 |
{
|
| 2 |
"lora_name": "charluv-lora",
|
| 3 |
-
"always_override":
|
| 4 |
-
"save_steps":
|
| 5 |
"micro_batch_size": 4,
|
| 6 |
-
"batch_size":
|
| 7 |
-
"epochs":
|
| 8 |
"learning_rate": "3e-4",
|
| 9 |
-
"lr_scheduler_type": "
|
| 10 |
"lora_rank": 128,
|
| 11 |
"lora_alpha": 256,
|
| 12 |
"lora_dropout": 0.05,
|
| 13 |
"cutoff_len": 256,
|
| 14 |
-
"dataset": "
|
| 15 |
"eval_dataset": "None",
|
| 16 |
-
"format": "
|
| 17 |
"eval_steps": 100.0,
|
| 18 |
-
"raw_text_file": "
|
| 19 |
-
"overlap_len": 128,
|
| 20 |
-
"newline_favor_len": 128,
|
| 21 |
"higher_rank_limit": false,
|
| 22 |
"warmup_steps": 100.0,
|
| 23 |
"optimizer": "adamw_torch",
|
| 24 |
"hard_cut_string": "\\n\\n\\n",
|
| 25 |
"train_only_after": "",
|
| 26 |
-
"stop_at_loss": 1
|
| 27 |
"add_eos_token": false,
|
| 28 |
"min_chars": 0.0,
|
| 29 |
-
"report_to": "
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 30 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"lora_name": "charluv-lora",
|
| 3 |
+
"always_override": true,
|
| 4 |
+
"save_steps": 1000.0,
|
| 5 |
"micro_batch_size": 4,
|
| 6 |
+
"batch_size": 0,
|
| 7 |
+
"epochs": 1.0,
|
| 8 |
"learning_rate": "3e-4",
|
| 9 |
+
"lr_scheduler_type": "linear",
|
| 10 |
"lora_rank": 128,
|
| 11 |
"lora_alpha": 256,
|
| 12 |
"lora_dropout": 0.05,
|
| 13 |
"cutoff_len": 256,
|
| 14 |
+
"dataset": "training",
|
| 15 |
"eval_dataset": "None",
|
| 16 |
+
"format": "alpaca-format",
|
| 17 |
"eval_steps": 100.0,
|
| 18 |
+
"raw_text_file": "None",
|
|
|
|
|
|
|
| 19 |
"higher_rank_limit": false,
|
| 20 |
"warmup_steps": 100.0,
|
| 21 |
"optimizer": "adamw_torch",
|
| 22 |
"hard_cut_string": "\\n\\n\\n",
|
| 23 |
"train_only_after": "",
|
| 24 |
+
"stop_at_loss": 0.1,
|
| 25 |
"add_eos_token": false,
|
| 26 |
"min_chars": 0.0,
|
| 27 |
+
"report_to": "None",
|
| 28 |
+
"precize_slicing_overlap": true,
|
| 29 |
+
"add_eos_token_type": "Every Block",
|
| 30 |
+
"save_steps_under_loss": 1.8,
|
| 31 |
+
"add_bos_token": true,
|
| 32 |
+
"training_projection": "all",
|
| 33 |
+
"sliding_window": false,
|
| 34 |
+
"warmup_ratio": 0,
|
| 35 |
+
"grad_accumulation": 1,
|
| 36 |
+
"neft_noise_alpha": 0
|
| 37 |
}
|
training_prompt.json
CHANGED
|
@@ -1,3 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"template_type": "
|
|
|
|
|
|
|
| 3 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"template_type": "dataset",
|
| 3 |
+
"template_1": "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n%instruction%\n\n### Response:\n%output%",
|
| 4 |
+
"template_2": "Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n%instruction%\n\n### Input:\n%input%\n\n### Response:\n%output%"
|
| 5 |
}
|