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enosislabs
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matex-privacy-sentinel-v0.1

Token Classification
Transformers
Safetensors
privacy_filter
privacy
pii
secrets
code-security
matex
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Upload matex-privacy-sentinel-v0.1 trained on Modal A10

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Files changed (6) hide show
  1. README.md +32 -0
  2. USAGE.txt +7 -0
  3. config.json +154 -0
  4. custom_label_space.json +30 -0
  5. finetune_summary.json +85 -0
  6. model.safetensors +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: openai/privacy-filter
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+ license: apache-2.0
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+ tags:
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+ - token-classification
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+ - privacy
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+ - pii
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+ - secrets
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+ - code-security
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+ - matex
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+ datasets:
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+ - enosislabs/matex-privacy-sentinel-dataset
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+ ---
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+
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+ # MaTE X Privacy Sentinel v0.1
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+
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+ Fine-tuned checkpoint based on OpenAI Privacy Filter for local privacy/security redaction in MaTE X.
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+
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+ ## Dataset
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+
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+ `enosislabs/matex-privacy-sentinel-dataset`
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+
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+ ## Usage
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+
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+ ```bash
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+ opf --checkpoint . "DATABASE_URL=postgres://demo_user:demo_pass@db.local/matex"
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+ ```
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+
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+ ## Limitation
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+
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+ This is a privacy/security aid, not a compliance guarantee. Run your own canary evaluation before production.
USAGE.txt ADDED
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+ Finetuned checkpoint generated by `opf train`.
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+
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+ Run local inference:
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+ opf --checkpoint /__modal/volumes/vo-XIgHS4JYPE8ddRlAcjQTwm/matex-privacy-sentinel-v0.1 --device cuda "Alice was born on 1990-01-02."
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+
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+ Run eval:
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+ opf eval /path/to/eval.jsonl --checkpoint /__modal/volumes/vo-XIgHS4JYPE8ddRlAcjQTwm/matex-privacy-sentinel-v0.1 --device cuda
config.json ADDED
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+ {
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+ "bidirectional_context": true,
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+ "bidirectional_left_context": 128,
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+ "bidirectional_right_context": 128,
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+ "category_version": "matex_privacy_sentinel_v0_1",
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+ "default_n_ctx": 128000,
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+ "encoding": "o200k_base",
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+ "experts_per_token": 4,
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+ "head_dim": 64,
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+ "hidden_size": 640,
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+ "inference_contract_version": 1,
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+ "initial_context_length": 4096,
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+ "intermediate_size": 640,
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+ "max_position_embeddings": 131072,
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+ "model_type": "privacy_filter",
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+ "ner_class_names": [
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+ "O",
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+ "B-account_number",
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+ "I-account_number",
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+ "E-account_number",
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+ "S-account_number",
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+ "B-private_address",
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+ "I-private_address",
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+ "E-private_address",
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+ "S-private_address",
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+ "B-private_email",
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+ "I-private_email",
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+ "E-private_email",
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+ "S-private_email",
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+ "B-private_person",
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+ "I-private_person",
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+ "E-private_person",
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+ "S-private_person",
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+ "B-private_phone",
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+ "I-private_phone",
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+ "E-private_phone",
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+ "S-private_phone",
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+ "B-private_url",
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+ "I-private_url",
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+ "E-private_url",
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+ "S-private_url",
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+ "B-private_date",
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+ "I-private_date",
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+ "E-private_date",
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+ "S-private_date",
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+ "B-secret",
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+ "I-secret",
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+ "E-secret",
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+ "S-secret",
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+ "B-api_key",
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+ "I-api_key",
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+ "E-api_key",
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+ "S-api_key",
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+ "B-auth_token",
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+ "I-auth_token",
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+ "E-auth_token",
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+ "S-auth_token",
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+ "B-session_cookie",
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+ "I-session_cookie",
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+ "E-session_cookie",
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+ "S-session_cookie",
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+ "B-database_uri",
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+ "I-database_uri",
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+ "E-database_uri",
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+ "S-database_uri",
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+ "B-cloud_credential",
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+ "I-cloud_credential",
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+ "E-cloud_credential",
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+ "S-cloud_credential",
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+ "B-env_value",
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+ "I-env_value",
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+ "E-env_value",
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+ "S-env_value",
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+ "B-private_file_path",
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+ "I-private_file_path",
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+ "E-private_file_path",
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+ "S-private_file_path",
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+ "B-internal_url",
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+ "I-internal_url",
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+ "E-internal_url",
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+ "S-internal_url",
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+ "B-workspace_identity",
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+ "I-workspace_identity",
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+ "E-workspace_identity",
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+ "S-workspace_identity",
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+ "B-customer_data",
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+ "I-customer_data",
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+ "E-customer_data",
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+ "S-customer_data",
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+ "B-prompt_sensitive",
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+ "I-prompt_sensitive",
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+ "E-prompt_sensitive",
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+ "S-prompt_sensitive",
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+ "B-agent_memory_sensitive",
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+ "I-agent_memory_sensitive",
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+ "E-agent_memory_sensitive",
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+ "S-agent_memory_sensitive",
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+ "B-stacktrace_sensitive",
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+ "I-stacktrace_sensitive",
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+ "E-stacktrace_sensitive",
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+ "S-stacktrace_sensitive",
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+ "B-repo_secret",
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+ "I-repo_secret",
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+ "E-repo_secret",
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+ "S-repo_secret",
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+ "B-payment_token",
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+ "I-payment_token",
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+ "E-payment_token",
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+ "S-payment_token",
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+ "B-personal_document_id",
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+ "I-personal_document_id",
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+ "E-personal_document_id",
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+ "S-personal_document_id"
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+ ],
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+ "num_attention_heads": 14,
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+ "num_experts": 128,
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+ "num_hidden_layers": 8,
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+ "num_key_value_heads": 2,
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+ "num_labels": 97,
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+ "param_dtype": "bfloat16",
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+ "rope_ntk_alpha": 1.0,
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+ "rope_ntk_beta": 32.0,
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+ "rope_scaling_factor": 32.0,
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+ "rope_theta": 150000,
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+ "sliding_window": 257,
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+ "span_class_names": [
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+ "O",
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+ "account_number",
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+ "private_address",
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+ "private_email",
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+ "private_person",
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+ "private_phone",
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+ "private_url",
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+ "private_date",
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+ "secret",
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+ "api_key",
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+ "auth_token",
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+ "session_cookie",
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+ "database_uri",
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+ "cloud_credential",
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+ "env_value",
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+ "private_file_path",
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+ "internal_url",
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+ "workspace_identity",
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+ "customer_data",
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+ "prompt_sensitive",
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+ "agent_memory_sensitive",
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+ "stacktrace_sensitive",
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+ "repo_secret",
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+ "payment_token",
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+ "personal_document_id"
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+ ],
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+ "vocab_size": 200064
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+ }
custom_label_space.json ADDED
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+ {
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+ "category_version": "matex_privacy_sentinel_v0_1",
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+ "span_class_names": [
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+ "O",
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+ "account_number",
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+ "private_address",
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+ "private_email",
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+ "private_person",
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+ "private_phone",
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+ "private_url",
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+ "private_date",
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+ "secret",
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+ "api_key",
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+ "auth_token",
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+ "session_cookie",
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+ "database_uri",
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+ "cloud_credential",
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+ "env_value",
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+ "private_file_path",
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+ "internal_url",
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+ "workspace_identity",
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+ "customer_data",
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+ "prompt_sensitive",
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+ "agent_memory_sensitive",
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+ "stacktrace_sensitive",
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+ "repo_secret",
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+ "payment_token",
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+ "personal_document_id"
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+ ]
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+ }
finetune_summary.json ADDED
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+ {
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+ "artifacts": {
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+ "config_json": "/__modal/volumes/vo-XIgHS4JYPE8ddRlAcjQTwm/matex-privacy-sentinel-v0.1/config.json",
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+ "model_safetensors": "/__modal/volumes/vo-XIgHS4JYPE8ddRlAcjQTwm/matex-privacy-sentinel-v0.1/model.safetensors",
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+ "summary_json": "/__modal/volumes/vo-XIgHS4JYPE8ddRlAcjQTwm/matex-privacy-sentinel-v0.1/finetune_summary.json"
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+ },
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+ "base_checkpoint": "/root/.opf/privacy_filter",
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+ "batch_size": 4,
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+ "best_epoch": 1,
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+ "best_metric": 7.897648645950944e-05,
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+ "best_metric_name": "validation_loss",
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+ "checkpoint_category_version": "v2",
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+ "device": "cuda",
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+ "elapsed_s": 223.644200789,
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+ "encoding": "o200k_base",
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+ "epoch_metrics": [
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+ "epoch": 1,
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+ "optimizer_steps": 1688,
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+ "train_batches": 1688,
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+ "train_loss": 0.07091577861013018,
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+ "train_token_accuracy": 0.9923756289082941,
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+ "train_tokens": 684122,
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+ "validation_batches": 94,
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+ "validation_loss": 7.897648645950944e-05,
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+ "validation_token_accuracy": 1.0,
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+ "validation_tokens": 36432
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+ }
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+ ],
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+ "epochs": 1,
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+ "generated_at_unix": 1777695794.6015186,
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+ "grad_accum_steps": 1,
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+ "label_space_json_path": "/__modal/volumes/vo-1GyZvIAPD7wnYD3s0C2QXS/dataset/configs/custom_label_space.json",
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+ "label_space_source": "label-space-json",
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+ "learning_rate": 1e-05,
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+ "max_grad_norm": 1.0,
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+ "num_output_labels": 97,
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+ "num_train_examples": 6750,
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+ "num_train_windows": 6750,
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+ "num_validation_examples": 375,
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+ "num_validation_windows": 375,
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+ "output_checkpoint_dir": "/__modal/volumes/vo-XIgHS4JYPE8ddRlAcjQTwm/matex-privacy-sentinel-v0.1",
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+ "output_head_reinitialized": true,
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+ "output_head_rows_copied": 97,
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+ "output_head_rows_copied_exact": 33,
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+ "output_head_rows_copied_fallback": 64,
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+ "resolved_category_version": "matex_privacy_sentinel_v0_1",
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+ "resolved_n_ctx": 128000,
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+ "schema_version": 1,
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+ "serialized_param_dtype": "bfloat16",
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+ "span_class_names": [
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+ "O",
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+ "account_number",
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+ "private_address",
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+ "private_email",
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+ "private_person",
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+ "private_phone",
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+ "private_url",
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+ "private_date",
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+ "secret",
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+ "api_key",
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+ "auth_token",
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+ "session_cookie",
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+ "database_uri",
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+ "cloud_credential",
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+ "env_value",
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+ "private_file_path",
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+ "internal_url",
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+ "workspace_identity",
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+ "customer_data",
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+ "prompt_sensitive",
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+ "agent_memory_sensitive",
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+ "stacktrace_sensitive",
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+ "repo_secret",
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+ "payment_token",
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+ "personal_document_id"
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+ ],
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+ "train_dataset": "/data/dataset/compiled/train.jsonl",
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+ "train_dataset_variant": "full",
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+ "validation_dataset": "/data/dataset/compiled/validation.jsonl",
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+ "validation_dataset_variant": "full",
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+ "validation_split": null,
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+ "weight_decay": 0.01
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+ }
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