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README.md

@@ -1,65 +1,207 @@
 ---
-license: apache-2.0
+base_model: LiquidAI/LFM2.5-350M
+library_name: peft
 pipeline_tag: text-generation
 tags:
-  - lfm2
-  - data-use
-  - data-mentions
-  - extraction
-  - sft
-  - lora
+- base_model:adapter:LiquidAI/LFM2.5-350M
+- lora
+- transformers
 ---
 
-# lfm2.5-350M-datause-prwp
-
-LoRA SFT of `LiquidAI/LFM2.5-350M` for data-mention extraction: emit the
-data-bearing phrases in a text as compact JSON
-(`data_mentions` with `data_mention`/`specificity_type`).
-
-## Training
-- base model: `LiquidAI/LFM2.5-350M`
-- dataset: `rafmacalaba/data-use-mention-sft`
-- epochs: 3
-- learning rate: 0.0002
-- LoRA: r=16 alpha=32 dropout=0.05
-- completion-only masking (loss on assistant JSON turn)
-
-## Evaluation (holdout, n=9079)
-
-Jaccard entity-level matching: acronym-aware span clustering +
-Hungarian optimal bipartite match (match thr=0.5), F0.5
-primary. Aligned with `rafmacalaba/gliner_datause_extended`. The
-holdout is `rafmacalaba/data-use-mention-sft`, so numbers are **not
-directly comparable** to the GLiNER model's `data-use-mentions-extended`
-holdout.
-
-| label | tp | fp | fn | precision | recall | f0.5 | f1 |
-| --- | --- | --- | --- | --- | --- | --- | --- |
-| **overall** | 9961 | 2581 | 2341 | 0.7942 | 0.8097 | 0.7973 | 0.8019 |
-## Per-corpus
-
-| label | tp | fp | fn | precision | recall | f0.5 | f1 |
-| --- | --- | --- | --- | --- | --- | --- | --- |
-| prwp | 9961 | 2581 | 2341 | 0.7942 | 0.8097 | 0.7973 | 0.8019 |
-## Per-origin
-
-| label | tp | fp | fn | precision | recall | f0.5 | f1 |
-| --- | --- | --- | --- | --- | --- | --- | --- |
-| general_prwp | 9961 | 2581 | 2341 | 0.7942 | 0.8097 | 0.7973 | 0.8019 |
-
-## Sample predictions (holdout)
-
-| gold | predicted |
-| --- | --- |
-| {"data_mentions":[{"data_mention":"administrative data","specificity_type":"descriptive"}]} | {"data_mentions":[{"data_mention":"administrative data","specificity_type":"descriptive"}]} |
-| {"data_mentions":[{"data_mention":"World Development Indicators","specificity_type":"named"},{"data_mention":"CPHS","spe | {"data_mentions":[{"data_mention":"World Development Indicators","specificity_type":"named"},{"data_mention":"CPHS","spe |
-| {"data_mentions":[{"data_mention":"ES data","specificity_type":"named"}]} | {"data_mentions":[{"data_mention":"ES data","specificity_type":"named"}]} |
-| {"data_mentions":[]} | {"data_mentions":[]} |
-| {"data_mentions":[{"data_mention":"World Development Indicators","specificity_type":"named"},{"data_mention":"IMF World  | {"data_mentions":[{"data_mention":"World Development Indicators","specificity_type":"named"},{"data_mention":"IMF World  |
-| {"data_mentions":[]} | {"data_mentions":[]} |
-| {"data_mentions":[{"data_mention":"UNESCO-provided data","specificity_type":"descriptive"}]} | {"data_mentions":[{"data_mention":"UNESCO-provided data","specificity_type":"named"}]} |
-| {"data_mentions":[{"data_mention":"IHPS dataset","specificity_type":"named"},{"data_mention":"IHS4 data","specificity_ty | {"data_mentions":[{"data_mention":"IHS4 dataset","specificity_type":"named"},{"data_mention":"IHS4 data","specificity_ty |
-| {"data_mentions":[{"data_mention":"HFSSS","specificity_type":"named"}]} | {"data_mentions":[{"data_mention":"HFSSS","specificity_type":"named"}]} |
-| {"data_mentions":[{"data_mention":"HFCS data","specificity_type":"named"}]} | {"data_mentions":[{"data_mention":"HFCS data","specificity_type":"named"}]} |
-| {"data_mentions":[{"data_mention":"data on patents and publications","specificity_type":"descriptive"}]} | {"data_mentions":[{"data_mention":"data on patents and publications related to climate friendly technologies","specifici |
-| {"data_mentions":[{"data_mention":"UN COMTRADE Statistics","specificity_type":"named"}]} | {"data_mentions":[{"data_mention":"UN COMTRADE Statistics","specificity_type":"named"}]} |
+# 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 0.20.0

adapter_config.json

@@ -31,14 +31,14 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "q_proj",
     "w1",
-    "out_proj",
-    "w2",
+    "k_proj",
     "v_proj",
+    "w2",
+    "q_proj",
+    "w3",
     "in_proj",
-    "k_proj",
-    "w3"
+    "out_proj"
   ],
   "target_parameters": null,
   "task_type": "CAUSAL_LM",

adapter_model.safetensors

@@ -1,3 +1,3 @@
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