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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,88 @@
+---
+license: apache-2.0
+language:
+- en
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+pipeline_tag: text-classification
+library_name: peft
+tags:
+- regression
+- story-point-estimation
+- software-engineering
+datasets:
+- appceleratorstudio
+metrics:
+- mae
+- mdae
+model-index:
+- name: DeepSeek-R1-Distill-Qwen-1.5B-story-point-estimation
+  results:
+  - task:
+      type: regression
+      name: Story Point Estimation
+    dataset:
+      name: appceleratorstudio Dataset
+      type: appceleratorstudio
+      split: test
+    metrics:
+    - type: mae
+      value: 1.689
+      name: Mean Absolute Error (MAE)
+    - type: mdae
+      value: 1.539
+      name: Median Absolute Error (MdAE)
+---
+# DeepSeek R1 Qwen Story Point Estimator - appceleratorstudio
+
+This model is fine-tuned on issue descriptions from appceleratorstudio and tested on appceleratorstudio for story point estimation.
+
+## Model Details
+- Base Model: DeepSeek R1 Distill Qwen 1.5B
+- Training Project: appceleratorstudio
+- Test Project: appceleratorstudio
+- Task: Story Point Estimation (Regression)
+- Architecture: PEFT (LoRA)
+- Tokenizer: DeepSeek BPE Tokenizer
+
+- Input: Issue titles
+- Output: Story point estimation (continuous value)
+
+## Usage
+```python
+from transformers import AutoModelForSequenceClassification
+from peft import PeftConfig, PeftModel
+from transformers import AutoTokenizer
+
+# Load peft config model
+config = PeftConfig.from_pretrained("DEVCamiloSepulveda/1-DeepSeekR1SP-appceleratorstudio")
+
+# Load tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("DEVCamiloSepulveda/1-DeepSeekR1SP-appceleratorstudio")
+base_model = AutoModelForSequenceClassification.from_pretrained(
+    config.base_model_name_or_path,
+    num_labels=1,
+    torch_dtype=torch.float16,
+    device_map='auto'
+)
+model = PeftModel.from_pretrained(base_model, "DEVCamiloSepulveda/1-DeepSeekR1SP-appceleratorstudio")
+
+# Prepare input text
+text = "Your issue description here"
+inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=20, padding="max_length")
+
+# Get prediction
+outputs = model(**inputs)
+story_points = outputs.logits.item()
+```
+
+## Training Details
+- Fine-tuning method: LoRA (Low-Rank Adaptation)
+- Sequence length: 20 tokens
+- Best training epoch: 0 / 20 epochs
+- Batch size: 32
+- Training time: 90.699 seconds
+- Mean Absolute Error (MAE): 1.689
+- Median Absolute Error (MdAE): 1.539
+### Framework versions
+
+- PEFT 0.14.0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
+  "bias": "none",
+  "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": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "classifier",
+    "score"
+  ],
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "o_proj",
+    "k_proj",
+    "q_proj"
+  ],
+  "task_type": "SEQ_CLS",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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pytorch_model.bin

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special_tokens_map.json

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+{
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "lstrip": false,
+    "normalized": false,
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+    "single_word": false
+  },
+  "pad_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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tokenizer_config.json

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+  "add_eos_token": false,
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+  "added_tokens_decoder": {
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<｜User｜>",
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+      "special": false
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+    "151645": {
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+    "151651": {
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+      "special": false
+    }
+  },
+  "bos_token": "<｜begin▁of▁sentence｜>",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<｜end▁of▁sentence｜>",
+  "extra_special_tokens": {},
+  "legacy": true,
+  "model_max_length": 16384,
+  "pad_token": "<｜end▁of▁sentence｜>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": null,
+  "use_default_system_prompt": false
+}