Upload Clinical Agent Transformer mcp-full artifacts

README.md

@@ -0,0 +1,301 @@
+---
+library_name: peft
+base_model: meta-llama/Llama-3.1-8B-Instruct
+tags:
+- llama
+- clinical-ai
+- antimicrobial-stewardship
+- tool-calling
+- peft
+- modal
+---
+
+# Clinical Agent Transformer
+
+This repository contains the trained artifacts for the Clinical Agent Transformer run:
+
+```text
+Repository: madan2248c/clinical-agent-transformer-llama-31-8b
+Stage: mcp
+Profile: full
+Base model: meta-llama/Llama-3.1-8B-Instruct
+```
+
+## What Is Included
+
+This upload contains the final trained package from the Modal checkpoint volume:
+
+- PEFT adapter files under `model/`
+- `trainable_state.pt` for the custom Clinical Agent Transformer modules
+- training metrics and graph-ready CSV files
+- training configuration
+
+The `trainable_state.pt` file is important because this project modifies the LLaMA architecture with custom MLA, MoE, recurrent, QK-Norm, post-norm, and MTP components. The adapter files alone do not represent every custom trainable module.
+
+## Training Procedure
+
+The model was trained in two stages:
+
+1. Clinical literacy training on the combined clinical corpus.
+2. MCP agentic tool-call training on balanced antimicrobial stewardship traces.
+
+The MCP full run resumes from the clinical full trainable state.
+
+## Reported Metrics
+
+```json
+{
+  "run_name": "clinical-agent-transformer-mcp-full",
+  "dataset_path": "/root/generated_data/amr_mcp_traces_balanced_v1.jsonl",
+  "dataset_records": 1800,
+  "train_records": 1620,
+  "validation_records": 180,
+  "text_field": "text_trace",
+  "resume_trainable_state": "/checkpoints/runs/clinical-agent-transformer-clinical-full/trainable_state.pt",
+  "seq_len": 1024,
+  "train_steps": 1200,
+  "gradient_accumulation_steps": 8,
+  "learning_rate": 2e-05,
+  "warmup_steps": 100,
+  "eval_every": 100,
+  "checkpoint_every": 0,
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+```
+
+## Intended Use
+
+This model package is intended for project demonstration, research, and evaluation of a clinical-agent transformer architecture. It is not intended for direct clinical deployment without external validation, safety testing, and expert review.

losses.csv

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+}

model/README.md

@@ -0,0 +1,207 @@
+---
+base_model: meta-llama/Llama-3.1-8B-Instruct
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:meta-llama/Llama-3.1-8B-Instruct
+- lora
+- transformers
+---
+
+# 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. -->
+
+
+
+- **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]
+### Framework versions
+
+- PEFT 0.19.1

model/adapter_config.json

@@ -0,0 +1,45 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "meta-llama/Llama-3.1-8B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj",
+    "k_proj",
+    "o_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

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trainable_state.pt

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training_config.json

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+  "model_name": "meta-llama/Llama-3.1-8B-Instruct",
+  "run_name": "clinical-agent-transformer-mcp-full",
+  "seq_len": 1024,
+  "micro_batch_size": 1,
+  "gradient_accumulation_steps": 8,
+  "learning_rate": 2e-05,
+  "train_steps": 1200,
+  "warmup_steps": 100,
+  "weight_decay": 0.01,
+  "use_bf16": true,
+  "gradient_checkpointing": true,
+  "hf_cache_dir": "/cache/huggingface",
+  "dataset_dir": "/root/generated_data",
+  "checkpoint_dir": "/checkpoints",
+  "output_dir": "/checkpoints/runs",
+  "train_jsonl": "/root/generated_data/amr_mcp_traces_balanced_v1.jsonl",
+  "text_field": "text_trace",
+  "max_records": null,
+  "validation_fraction": 0.1,
+  "resume_trainable_state": "/checkpoints/runs/clinical-agent-transformer-clinical-full/trainable_state.pt",
+  "log_every": 25,
+  "eval_every": 100,
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+  "max_eval_batches": 75,
+  "seed": 42,
+  "optimizer_name": "adam8bit",
+  "freeze_base_model": false,
+  "adapter": "AdapterConfig(enabled=True, adapter_name='clinical_agent_adapter', r=8, lora_alpha=32, lora_dropout=0.05, target_modules=('q_proj', 'k_proj', 'v_proj', 'o_proj'))",
+  "surgery": "SurgeryConfig(use_mla=True, use_qk_norm=True, use_post_norm=True, use_moe_layers=True, use_recurrent_layers=True, use_mtp_head=True, qk_norm_layers=(), qk_norm_eps=1e-05, mla_layers=(), moe_layers=(), recurrent_layers=())"
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