Instructions to use TheAgenticAI/Agentic-V4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use TheAgenticAI/Agentic-V4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Nexusflow/Athene-V2-Agent") model = PeftModel.from_pretrained(base_model, "TheAgenticAI/Agentic-V4") - Notebooks
- Google Colab
- Kaggle
Upload Agentic-V4
Browse files- README.md +202 -0
- adapter_config.json +30 -0
- adapter_model.safetensors +3 -0
- additional_config.json +1 -0
- configuration.json +11 -0
- generation_config.json +9 -0
- optimizer.pt +3 -0
- rng_state_0.pth +3 -0
- rng_state_1.pth +3 -0
- scheduler.pt +3 -0
- sft_args.json +275 -0
- trainer_state.json +433 -0
- training_args.bin +3 -0
README.md
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---
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base_model: Nexusflow/Athene-V2-Agent
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library_name: peft
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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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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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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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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [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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### 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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[More Information Needed]
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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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[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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<!-- 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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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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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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[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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[More Information Needed]
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### Framework versions
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- PEFT 0.12.0
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "Nexusflow/Athene-V2-Agent",
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"bias": "none",
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| 6 |
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"fan_in_fan_out": false,
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| 7 |
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"inference_mode": true,
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| 8 |
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"init_lora_weights": true,
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| 9 |
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"layer_replication": null,
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| 10 |
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 64,
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| 14 |
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"lora_dropout": 0.2,
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| 15 |
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"megatron_config": null,
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| 16 |
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"megatron_core": "megatron.core",
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| 17 |
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"modules_to_save": [],
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| 18 |
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"peft_type": "LORA",
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| 19 |
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"r": 32,
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"rank_pattern": {},
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| 21 |
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"revision": null,
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| 22 |
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"target_modules": [
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| 23 |
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"q_proj",
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| 24 |
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"v_proj",
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| 25 |
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"k_proj"
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| 26 |
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],
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| 27 |
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"task_type": "CAUSAL_LM",
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| 28 |
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6534f304ad85cc7d48e281715fd82923fd15a5432fdb6fcb625b1c4f82abdc3f
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size 356581280
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additional_config.json
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{"lora_dtype": null, "lorap_lr_ratio": null, "lorap_emb_lr": 1e-06}
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configuration.json
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{
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"adapter_cfg": {
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"model_id_or_path": "/root/dataDisk/ms-swift/models",
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"model_revision": "master",
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"sft_type": "lora",
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"tuner_backend": "peft",
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"template_type": "qwen2_5",
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"dtype": "bf16",
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"system": ""
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}
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}
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generation_config.json
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{
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"bos_token_id": 151643,
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"do_sample": true,
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"eos_token_id": 151645,
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"max_new_tokens": 2048,
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"pad_token_id": 151643,
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"temperature": 0.7,
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"transformers_version": "4.46.3"
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}
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optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:ba9f4df36b64eee4d5f4db32a3ce052e7935fe817f4d209e5108da05bf5fbdad
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size 713436530
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rng_state_0.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:575119a228f98110923ffa2dedcb50e3317251b26054355d015e0b2240d566f2
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size 15984
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rng_state_1.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:bc091d2c64e295da198fc50a521da2b2e71efaede488211abd625b6121c779b1
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size 15920
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scheduler.pt
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:3b1a976c61366775f17b2f4ed938a496722f9b6544db424f2d3f492fcf2b4b9d
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| 3 |
+
size 1064
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sft_args.json
ADDED
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@@ -0,0 +1,275 @@
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|
| 1 |
+
{
|
| 2 |
+
"model_type": "qwen2_5-72b-instruct",
|
| 3 |
+
"model_id_or_path": "/root/dataDisk/ms-swift/models",
|
| 4 |
+
"model_revision": "master",
|
| 5 |
+
"full_determinism": false,
|
| 6 |
+
"sft_type": "lora",
|
| 7 |
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"freeze_parameters": [],
|
| 8 |
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"freeze_vit": false,
|
| 9 |
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"freeze_parameters_ratio": 0.0,
|
| 10 |
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"additional_trainable_parameters": [],
|
| 11 |
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"tuner_backend": "peft",
|
| 12 |
+
"template_type": "qwen2_5",
|
| 13 |
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"output_dir": "/root/dataDisk/ms-swift/new_train/qwen2_5-72b-instruct/v7-20241210-142056",
|
| 14 |
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"add_output_dir_suffix": true,
|
| 15 |
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"ddp_backend": "nccl",
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| 16 |
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"ddp_find_unused_parameters": null,
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| 17 |
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"ddp_broadcast_buffers": null,
|
| 18 |
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"ddp_timeout": 1800,
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| 19 |
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"seed": 42,
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| 20 |
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"resume_from_checkpoint": null,
|
| 21 |
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"resume_only_model": false,
|
| 22 |
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"ignore_data_skip": false,
|
| 23 |
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"dtype": "bf16",
|
| 24 |
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"packing": false,
|
| 25 |
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"train_backend": "transformers",
|
| 26 |
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"tp": 1,
|
| 27 |
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"pp": 1,
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| 28 |
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"min_lr": null,
|
| 29 |
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"sequence_parallel": false,
|
| 30 |
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"model_kwargs": {},
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| 31 |
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"loss_name": null,
|
| 32 |
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"dataset": [
|
| 33 |
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"merged_data.jsonl"
|
| 34 |
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],
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| 35 |
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"val_dataset": [],
|
| 36 |
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"dataset_seed": 42,
|
| 37 |
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"dataset_test_ratio": 0.01,
|
| 38 |
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"use_loss_scale": false,
|
| 39 |
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"loss_scale_config_path": "/root/dataDisk/.venv/lib/python3.12/site-packages/swift/llm/agent/default_loss_scale_config.json",
|
| 40 |
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"system": "",
|
| 41 |
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"tools_prompt": "react_en",
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| 42 |
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"max_length": 15000,
|
| 43 |
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"truncation_strategy": "delete",
|
| 44 |
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"check_dataset_strategy": "none",
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| 45 |
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"streaming": false,
|
| 46 |
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"streaming_val_size": 0,
|
| 47 |
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"streaming_buffer_size": 16384,
|
| 48 |
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"model_name": [
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| 49 |
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null,
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| 50 |
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null
|
| 51 |
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],
|
| 52 |
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"model_author": [
|
| 53 |
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null,
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| 54 |
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null
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| 55 |
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],
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| 56 |
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"quant_method": null,
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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"bnb_4bit_comp_dtype": "bf16",
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| 61 |
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"bnb_4bit_quant_type": "nf4",
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| 62 |
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|
| 63 |
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"bnb_4bit_quant_storage": null,
|
| 64 |
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"rescale_image": -1,
|
| 65 |
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"target_modules": [
|
| 66 |
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"q_proj",
|
| 67 |
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"k_proj",
|
| 68 |
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"v_proj"
|
| 69 |
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],
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| 70 |
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"target_regex": null,
|
| 71 |
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"modules_to_save": [],
|
| 72 |
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"lora_rank": 32,
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| 73 |
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| 74 |
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| 75 |
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| 76 |
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| 77 |
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|
| 78 |
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| 79 |
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| 80 |
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| 81 |
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| 82 |
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| 83 |
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|
| 84 |
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| 85 |
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| 86 |
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| 87 |
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| 88 |
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"vera_rank": 256,
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| 89 |
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| 90 |
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"vera_dropout": 0.0,
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| 91 |
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| 92 |
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"adapter_act": "gelu",
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| 93 |
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"adapter_length": 128,
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| 94 |
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"use_galore": false,
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| 95 |
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"galore_target_modules": null,
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| 96 |
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"galore_rank": 128,
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| 97 |
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"galore_update_proj_gap": 50,
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| 98 |
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"galore_scale": 1.0,
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| 99 |
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"galore_proj_type": "std",
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| 100 |
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"galore_optim_per_parameter": false,
|
| 101 |
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"galore_with_embedding": false,
|
| 102 |
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"galore_quantization": false,
|
| 103 |
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"galore_proj_quant": false,
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| 104 |
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"galore_proj_bits": 4,
|
| 105 |
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"galore_proj_group_size": 256,
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| 106 |
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"galore_cos_threshold": 0.4,
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| 107 |
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"galore_gamma_proj": 2,
|
| 108 |
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"galore_queue_size": 5,
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| 109 |
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"adalora_target_r": 8,
|
| 110 |
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"adalora_init_r": 12,
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| 111 |
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"adalora_tinit": 0,
|
| 112 |
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"adalora_tfinal": 0,
|
| 113 |
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"adalora_deltaT": 1,
|
| 114 |
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"adalora_beta1": 0.85,
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| 115 |
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"adalora_beta2": 0.85,
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| 116 |
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"adalora_orth_reg_weight": 0.5,
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| 117 |
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"ia3_feedforward_modules": [],
|
| 118 |
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"llamapro_num_new_blocks": 4,
|
| 119 |
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"llamapro_num_groups": null,
|
| 120 |
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"neftune_noise_alpha": null,
|
| 121 |
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"neftune_backend": "transformers",
|
| 122 |
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"lisa_activated_layers": 0,
|
| 123 |
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"lisa_step_interval": 20,
|
| 124 |
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"reft_layer_key": null,
|
| 125 |
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|
| 126 |
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"reft_rank": 4,
|
| 127 |
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"reft_intervention_type": "LoreftIntervention",
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| 128 |
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"reft_args": null,
|
| 129 |
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"use_liger": false,
|
| 130 |
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"gradient_checkpointing": true,
|
| 131 |
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"vit_use_gc": true,
|
| 132 |
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"deepspeed": null,
|
| 133 |
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"batch_size": 1,
|
| 134 |
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"eval_batch_size": 1,
|
| 135 |
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"auto_find_batch_size": false,
|
| 136 |
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"num_train_epochs": 1,
|
| 137 |
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"max_steps": -1,
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| 138 |
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"optim": "adamw_torch",
|
| 139 |
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"adam_beta1": 0.9,
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| 140 |
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"adam_beta2": 0.95,
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| 141 |
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"adam_epsilon": 1e-08,
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| 142 |
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"learning_rate": 0.0003,
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| 143 |
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"weight_decay": 0.01,
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| 144 |
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"gradient_accumulation_steps": 8,
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| 145 |
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"max_grad_norm": 1,
|
| 146 |
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"predict_with_generate": false,
|
| 147 |
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"lr_scheduler_type": "cosine",
|
| 148 |
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"lr_scheduler_kwargs": {},
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| 149 |
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"warmup_ratio": 0.1,
|
| 150 |
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| 151 |
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| 152 |
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| 153 |
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| 154 |
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| 155 |
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"logging_steps": 1,
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| 156 |
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"acc_steps": 1,
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| 157 |
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"dataloader_num_workers": 1,
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| 158 |
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"dataloader_pin_memory": true,
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| 159 |
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| 160 |
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"push_to_hub": false,
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| 161 |
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| 162 |
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"hub_token": null,
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| 163 |
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| 164 |
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| 165 |
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|
| 166 |
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"disable_tqdm": false,
|
| 167 |
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|
| 168 |
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"preprocess_num_proc": 1,
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| 169 |
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"use_flash_attn": null,
|
| 170 |
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|
| 171 |
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"check_model_is_latest": true,
|
| 172 |
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"logging_dir": "/root/dataDisk/ms-swift/new_train/qwen2_5-72b-instruct/v7-20241210-142056/runs",
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| 173 |
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"report_to": [
|
| 174 |
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"all"
|
| 175 |
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],
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| 176 |
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"acc_strategy": "token",
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| 177 |
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"save_on_each_node": false,
|
| 178 |
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"evaluation_strategy": "steps",
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| 179 |
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| 180 |
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| 181 |
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| 182 |
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| 183 |
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| 184 |
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| 189 |
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| 190 |
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| 253 |
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| 255 |
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| 256 |
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| 257 |
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| 258 |
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| 262 |
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| 263 |
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|
| 275 |
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}
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trainer_state.json
ADDED
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training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:474087e8f80a856e73387c2f5cce01ee5d955732f9ded1e4682050c9ae86c816
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| 3 |
+
size 7672
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