Initial model upload

README.md

@@ -1,3 +1,62 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- text-classification
+- log-analysis
+- openstack
+- distilbert
+- fine-tuned
+datasets:
+- custom
+language:
+- en
+pipeline_tag: text-classification
+---
+
+# INFRNCE BERT Log Classification Model
+
+This is a fine-tuned DistilBERT model for classifying OpenStack Nova log entries into different operational categories.
+
+## Model Details
+
+- **Base Model**: distilbert-base-uncased
+- **Task**: Multi-class text classification
+- **Number of Labels**: 6
+- **Domain**: OpenStack log analysis
+
+## Labels
+
+The model classifies logs into the following categories:
+
+- Error_Handling, - Instance_Management, - Network_Operations, - Resource_Management, - Scheduler_Operations, - System_Operations
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# Load the model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("your-username/infrnce-bert-log-classifier")
+model = AutoModelForSequenceClassification.from_pretrained("your-username/infrnce-bert-log-classifier")
+
+# Example usage
+log_text = "Your OpenStack log entry here"
+inputs = tokenizer(log_text, return_tensors="pt", truncation=True, padding=True, max_length=512)
+
+with torch.no_grad():
+    outputs = model(**inputs)
+    predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
+    predicted_class_id = predictions.argmax().item()
+
+print(f"Predicted class: {model.config.id2label[predicted_class_id]}")
+```
+
+## Training Data
+
+The model was trained on a curated dataset of OpenStack Nova logs with both regex-based classifications and semantic clustering.
+
+## Performance
+
+The model was trained with controlled accuracy to achieve optimal performance on log classification tasks.

config.json

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+{
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "Error_Handling",
+    "1": "Instance_Management",
+    "2": "Network_Operations",
+    "3": "Resource_Management",
+    "4": "Scheduler_Operations",
+    "5": "System_Operations"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "Error_Handling": 0,
+    "Instance_Management": 1,
+    "Network_Operations": 2,
+    "Resource_Management": 3,
+    "Scheduler_Operations": 4,
+    "System_Operations": 5
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.52.4",
+  "vocab_size": 30522
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ab781f978a05e0b0db557e066a1f8fdc1bef2805c41fd62f4c0cae585b900855
+size 267844872

model_card.json

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+{
+  "model_type": "distilbert",
+  "task": "text-classification",
+  "tags": [
+    "log-analysis",
+    "openstack",
+    "text-classification"
+  ],
+  "base_model": "distilbert-base-uncased",
+  "num_labels": 6,
+  "labels": [
+    "Error_Handling",
+    "Instance_Management",
+    "Network_Operations",
+    "Resource_Management",
+    "Scheduler_Operations",
+    "System_Operations"
+  ],
+  "id2label": {
+    "0": "Error_Handling",
+    "1": "Instance_Management",
+    "2": "Network_Operations",
+    "3": "Resource_Management",
+    "4": "Scheduler_Operations",
+    "5": "System_Operations"
+  },
+  "label2id": {
+    "Error_Handling": 0,
+    "Instance_Management": 1,
+    "Network_Operations": 2,
+    "Resource_Management": 3,
+    "Scheduler_Operations": 4,
+    "System_Operations": 5
+  }
+}

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}