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  ---
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- library_name: transformers
 
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  tags:
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  - trl
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  - sft
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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- ## Model Details
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-
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- ### Model Description
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-
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- ## Uses
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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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-
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- ### Direct Use
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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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- [More Information Needed]
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- ### Downstream Use [optional]
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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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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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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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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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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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- [More Information Needed]
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- ### Training Procedure
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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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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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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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- <!-- This should link to a Dataset Card if possible. -->
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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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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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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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- 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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- ### Compute Infrastructure
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- #### Hardware
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- #### Software
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- ## Citation [optional]
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- **BibTeX:**
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- ## Glossary [optional]
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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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- [More Information Needed]
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  ---
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+ license: apache-2.0
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+ library_name: peft
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  tags:
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  - trl
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  - sft
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+ - generated_from_trainer
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+ base_model: mistralai/Mistral-7B-v0.1
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+ model-index:
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+ - name: lc_full
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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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+
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+ # lc_full
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.8715
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+
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+ ## Model description
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-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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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - num_epochs: 50
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+
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 1.7424 | 1.0 | 486 | 1.6914 |
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+ | 1.301 | 2.0 | 972 | 1.6780 |
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+ | 1.5718 | 3.0 | 1458 | 1.6743 |
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+ | 1.6632 | 4.0 | 1944 | 1.6793 |
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+ | 1.8588 | 5.0 | 2430 | 1.6794 |
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+ | 1.5308 | 6.0 | 2916 | 1.6894 |
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+ | 1.5776 | 7.0 | 3402 | 1.6985 |
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+ | 1.6394 | 8.0 | 3888 | 1.7073 |
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+ | 1.4696 | 9.0 | 4374 | 1.7187 |
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+ | 1.4191 | 10.0 | 4860 | 1.7298 |
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+ | 1.4776 | 11.0 | 5346 | 1.7414 |
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+ | 1.4767 | 12.0 | 5832 | 1.7512 |
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+ | 1.3546 | 13.0 | 6318 | 1.7731 |
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+ | 1.542 | 14.0 | 6804 | 1.7610 |
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+ | 1.3709 | 15.0 | 7290 | 1.7679 |
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+ | 1.3167 | 16.0 | 7776 | 1.7936 |
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+ | 1.3563 | 17.0 | 8262 | 1.8007 |
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+ | 1.4615 | 18.0 | 8748 | 1.8008 |
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+ | 1.511 | 19.0 | 9234 | 1.8068 |
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+ | 1.3145 | 20.0 | 9720 | 1.8232 |
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+ | 1.1285 | 21.0 | 10206 | 1.8204 |
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+ | 1.5045 | 22.0 | 10692 | 1.8204 |
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+ | 1.2697 | 23.0 | 11178 | 1.8453 |
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+ | 1.302 | 24.0 | 11664 | 1.8386 |
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+ | 1.4892 | 25.0 | 12150 | 1.8434 |
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+ | 1.5042 | 26.0 | 12636 | 1.8471 |
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+ | 1.1989 | 27.0 | 13122 | 1.8472 |
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+ | 1.2353 | 28.0 | 13608 | 1.8545 |
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+ | 1.145 | 29.0 | 14094 | 1.8560 |
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+ | 1.4146 | 30.0 | 14580 | 1.8612 |
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+ | 1.3598 | 31.0 | 15066 | 1.8611 |
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+ | 1.2659 | 32.0 | 15552 | 1.8695 |
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+ | 1.2085 | 33.0 | 16038 | 1.8631 |
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+ | 1.0623 | 34.0 | 16524 | 1.8679 |
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+ | 1.4594 | 35.0 | 17010 | 1.8694 |
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+ | 1.3038 | 36.0 | 17496 | 1.8685 |
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+ | 1.5902 | 37.0 | 17982 | 1.8695 |
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+ | 1.2771 | 38.0 | 18468 | 1.8709 |
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+ | 1.2738 | 39.0 | 18954 | 1.8698 |
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+ | 1.3209 | 40.0 | 19440 | 1.8707 |
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+ | 1.2578 | 41.0 | 19926 | 1.8709 |
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+ | 1.1108 | 42.0 | 20412 | 1.8717 |
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+ | 1.3264 | 43.0 | 20898 | 1.8711 |
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+ | 1.3152 | 44.0 | 21384 | 1.8709 |
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+ | 1.4287 | 45.0 | 21870 | 1.8709 |
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+ | 1.299 | 46.0 | 22356 | 1.8709 |
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+ | 1.2863 | 47.0 | 22842 | 1.8710 |
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+ | 1.1795 | 48.0 | 23328 | 1.8716 |
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+ | 1.27 | 49.0 | 23814 | 1.8719 |
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+ | 1.3156 | 50.0 | 24300 | 1.8715 |
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.41.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1