emdemor
/

guru1984

PEFT

Safetensors

trl

sft

Generated from Trainer

Model card Files Files and versions Community

emdemor commited on 27 days ago

Commit

5d237d8

•

1 Parent(s): 483efc1

Model save

Browse files

Files changed (1) hide show

README.md +96 -196

README.md CHANGED Viewed

@@ -1,199 +1,99 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-[More Information Needed]
-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- 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. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-[More Information Needed]
-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
-<!-- This should link to a Dataset Card if possible. -->
-[More Information Needed]
-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-[More Information Needed]
-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-[More Information Needed]
-### Results
-[More Information Needed]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-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).
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
+base_model: microsoft/Phi-3.5-mini-instruct
+library_name: peft
+license: mit
+tags:
+- trl
+- sft
+- generated_from_trainer
+model-index:
+- name: guru1984
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# guru1984
+This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9331
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 0.0005
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 4.0802        | 0.0786 | 50   | 3.3923          |
+| 2.6833        | 0.1572 | 100  | 2.3272          |
+| 2.1534        | 0.2358 | 150  | 2.1625          |
+| 2.0476        | 0.3145 | 200  | 2.1005          |
+| 1.9929        | 0.3931 | 250  | 2.0717          |
+| 1.974         | 0.4717 | 300  | 2.0509          |
+| 1.9854        | 0.5503 | 350  | 2.0435          |
+| 2.0109        | 0.6289 | 400  | 2.0358          |
+| 1.9939        | 0.7075 | 450  | 2.0285          |
+| 1.9672        | 0.7862 | 500  | 2.0150          |
+| 1.9565        | 0.8648 | 550  | 2.0115          |
+| 1.9706        | 0.9434 | 600  | 2.0062          |
+| 1.9352        | 1.0220 | 650  | 1.9949          |
+| 1.8647        | 1.1006 | 700  | 1.9930          |
+| 1.9109        | 1.1792 | 750  | 1.9840          |
+| 1.885         | 1.2579 | 800  | 1.9806          |
+| 1.8864        | 1.3365 | 850  | 1.9878          |
+| 1.8931        | 1.4151 | 900  | 1.9825          |
+| 1.8599        | 1.4937 | 950  | 1.9755          |
+| 1.9019        | 1.5723 | 1000 | 1.9695          |
+| 1.9081        | 1.6509 | 1050 | 1.9599          |
+| 1.8736        | 1.7296 | 1100 | 1.9583          |
+| 1.8939        | 1.8082 | 1150 | 1.9567          |
+| 1.8867        | 1.8868 | 1200 | 1.9534          |
+| 1.8875        | 1.9654 | 1250 | 1.9479          |
+| 1.8677        | 2.0440 | 1300 | 1.9498          |
+| 1.8152        | 2.1226 | 1350 | 1.9527          |
+| 1.8573        | 2.2013 | 1400 | 1.9523          |
+| 1.8433        | 2.2799 | 1450 | 1.9441          |
+| 1.828         | 2.3585 | 1500 | 1.9455          |
+| 1.8298        | 2.4371 | 1550 | 1.9423          |
+| 1.8258        | 2.5157 | 1600 | 1.9376          |
+| 1.8314        | 2.5943 | 1650 | 1.9373          |
+| 1.8436        | 2.6730 | 1700 | 1.9394          |
+| 1.8253        | 2.7516 | 1750 | 1.9373          |
+| 1.8055        | 2.8302 | 1800 | 1.9365          |
+| 1.8207        | 2.9088 | 1850 | 1.9342          |
+| 1.8514        | 2.9874 | 1900 | 1.9331          |
+### Framework versions
+- PEFT 0.12.0
+- Transformers 4.44.0
+- Pytorch 2.4.0
+- Datasets 2.21.0
+- Tokenizers 0.19.1