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.ipynb_checkpoints/README-checkpoint.md ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # 🤖 Thoth Text Model
2
+
3
+ ## 📘 Overview
4
+ **Thoth Text** هو نموذج لغوي عربي مبني على **[Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)**
5
+ تم تدريبه باستخدام تقنية **LoRA (Low-Rank Adaptation)** لتحسين الأداء في فهم النصوص العربية
6
+ وتوليد إجابات دقيقة في المجالات العامة والتعليمية.
7
+
8
+ ---
9
+
10
+ ## 🧠 Base Model
11
+ - **Base:** `Qwen/Qwen2.5-7B-Instruct`
12
+ - **Adapter:** LoRA fine-tuned using **Axolotl**
13
+ - **Architecture:** Transformer Decoder (Causal LM)
14
+ - **Precision:** `bfloat16`
15
+ - **Frameworks:** PyTorch + Transformers + PEFT
16
+
17
+ ---
18
+
19
+ ## 🏋️ Fine-tuning Details
20
+ - **Library:** [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
21
+ - **Adapter Type:** LoRA
22
+ - **Learning Rate:** `2e-4`
23
+ - **LoRA α:** `16`
24
+ - **LoRA r:** `8`
25
+ - **Dropout:** `0.05`
26
+ - **Batch Size:** `16`
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+ - **Epochs:** `1`
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+ - **Optimizer:** `adamw_bnb_8bit`
29
+ - **Sequence Length:** `4096`
30
+ - **Compute:** RunPod GPU Instance
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+
32
+ ---
33
+
34
+ ## 📂 Dataset
35
+ > ⚠️ **Note:**
36
+ > The dataset used for fine-tuning is **private and locally stored** at
37
+ > `/workspace/fine-tuning/data/trump.json`
38
+ >
39
+ > It follows the **Alpaca-style JSON format**:
40
+
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+ ```json
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+ [
43
+ {
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+ "instruction": "اشرح لي مفهوم الذكاء الاصطناعي.",
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+ "input": "",
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+ "output": "الذكاء الاصطناعي هو فرع من علوم الحاسوب يهتم بجعل الأنظمة قادرة على التفكير والتعلم."
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+ }
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+ ]
README.md CHANGED
@@ -1,3 +1,48 @@
1
- ---
2
- license: apache-2.0
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # 🤖 Thoth Text Model
2
+
3
+ ## 📘 Overview
4
+ **Thoth Text** هو نموذج لغوي عربي مبني على **[Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)**
5
+ تم تدريبه باستخدام تقنية **LoRA (Low-Rank Adaptation)** لتحسين الأداء في فهم النصوص العربية
6
+ وتوليد إجابات دقيقة في المجالات العامة والتعليمية.
7
+
8
+ ---
9
+
10
+ ## 🧠 Base Model
11
+ - **Base:** `Qwen/Qwen2.5-7B-Instruct`
12
+ - **Adapter:** LoRA fine-tuned using **Axolotl**
13
+ - **Architecture:** Transformer Decoder (Causal LM)
14
+ - **Precision:** `bfloat16`
15
+ - **Frameworks:** PyTorch + Transformers + PEFT
16
+
17
+ ---
18
+
19
+ ## 🏋️ Fine-tuning Details
20
+ - **Library:** [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
21
+ - **Adapter Type:** LoRA
22
+ - **Learning Rate:** `2e-4`
23
+ - **LoRA α:** `16`
24
+ - **LoRA r:** `8`
25
+ - **Dropout:** `0.05`
26
+ - **Batch Size:** `16`
27
+ - **Epochs:** `1`
28
+ - **Optimizer:** `adamw_bnb_8bit`
29
+ - **Sequence Length:** `4096`
30
+ - **Compute:** RunPod GPU Instance
31
+
32
+ ---
33
+
34
+ ## 📂 Dataset
35
+ > ⚠️ **Note:**
36
+ > The dataset used for fine-tuning is **private and locally stored** at
37
+ > `/workspace/fine-tuning/data/trump.json`
38
+ >
39
+ > It follows the **Alpaca-style JSON format**:
40
+
41
+ ```json
42
+ [
43
+ {
44
+ "instruction": "اشرح لي مفهوم الذكاء الاصطناعي.",
45
+ "input": "",
46
+ "output": "الذكاء الاصطناعي هو فرع من علوم الحاسوب يهتم بجعل الأنظمة قادرة على التفكير والتعلم."
47
+ }
48
+ ]
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1
+ ---
2
+ base_model: Qwen/Qwen2.5-7B-Instruct
3
+ library_name: peft
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+ pipeline_tag: text-generation
5
+ tags:
6
+ - axolotl
7
+ - base_model:adapter:Qwen/Qwen2.5-7B-Instruct
8
+ - lora
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+ - transformers
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
15
+
16
+
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+
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+ ## Model Details
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+
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+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
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+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+
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+ ### Direct Use
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+
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+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+
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+ [More Information Needed]
57
+
58
+ ### Out-of-Scope Use
59
+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
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+ [More Information Needed]
63
+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
81
+
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+ ## Training Details
83
+
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+ ### Training Data
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+
86
+ <!-- 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. -->
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+
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+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
98
+
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+ #### Training Hyperparameters
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+
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+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
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+ #### Speeds, Sizes, Times [optional]
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+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+
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+ #### Testing Data
116
+
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+ <!-- This should link to a Dataset Card if possible. -->
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+
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+ [More Information Needed]
120
+
121
+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
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+ [More Information Needed]
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+
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+ #### Metrics
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+
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+
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+ [More Information Needed]
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+
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+ ### Results
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+
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+ [More Information Needed]
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+
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+ #### Summary
138
+
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+
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+
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+ ## Model Examination [optional]
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+
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+ <!-- Relevant interpretability work for the model goes here -->
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+
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+ [More Information Needed]
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+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ 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).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
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+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
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+ [More Information Needed]
164
+
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+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
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+
169
+ #### Hardware
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+
171
+ [More Information Needed]
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+
173
+ #### Software
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+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
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+ [More Information Needed]
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+
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+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Contact
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+
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+ [More Information Needed]
206
+ ### Framework versions
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+
208
+ - PEFT 0.17.1
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+ [2025-10-22 16:34:25,444] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:278] [PID:2199] EOS: 151645 / <|im_end|>
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+ [2025-10-22 16:34:25,444] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:279] [PID:2199] BOS: None / None
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+ [2025-10-22 16:34:25,444] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:280] [PID:2199] PAD: 151643 / <|endoftext|>
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+ [2025-10-22 16:34:25,444] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:281] [PID:2199] UNK: None / None
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+ [2025-10-22 16:34:25,445] [INFO] [axolotl.utils.data.shared.load_preprocessed_dataset:476] [PID:2199] Unable to find prepared dataset in last_run_prepared/8eaeba3b90268710df560cd4dfe04e2d
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+ [2025-10-22 16:34:25,445] [INFO] [axolotl.utils.data.sft._load_raw_datasets:320] [PID:2199] Loading raw datasets...
134
+ [2025-10-22 16:34:25,445] [WARNING] [axolotl.utils.data.sft._load_raw_datasets:322] [PID:2199] Processing datasets during training can lead to VRAM instability. Please pre-process your dataset using `axolotl preprocess path/to/config.yml`.
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+ [2025-10-22 16:34:25,754] [INFO] [axolotl.utils.data.wrappers.get_dataset_wrapper:87] [PID:2199] Loading dataset: /workspace/fine-tuning/data/trump.json with base_type: alpaca and prompt_style: None
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+ [2025-10-22 16:34:25,754] [WARNING] [datasets.arrow_dataset.map:3100] [PID:2199] num_proc must be <= 15. Reducing num_proc to 15 for dataset of size 15.
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+ [2025-10-22 16:34:27,601] [WARNING] [datasets.arrow_dataset.map:3100] [PID:2199] num_proc must be <= 15. Reducing num_proc to 15 for dataset of size 15.
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+ [2025-10-22 16:34:28,163] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:404] [PID:2199] total_num_tokens: 1_016
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+ [2025-10-22 16:34:28,772] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:281] [PID:2199] UNK: None / None
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+ [2025-10-22 16:34:28,772] [DEBUG] [axolotl.train.setup_model_and_tokenizer:74] [PID:2199] Loading model
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+ [2025-10-22 16:34:28,895] [DEBUG] [axolotl.monkeypatch.transformers.trainer_loss_calc.patch_maybe_log_save_evaluate:138] [PID:2199] Patched Trainer._maybe_log_save_evaluate with nanmean loss calculation
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+ [2025-10-22 16:35:11,043] [INFO] [axolotl.loaders.model._prepare_model_for_quantization:863] [PID:2199] converting PEFT model w/ prepare_model_for_kbit_training
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+ [2025-10-22 16:35:11,045] [INFO] [axolotl.loaders.model._configure_embedding_dtypes:345] [PID:2199] Converting modules to torch.bfloat16
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+ [2025-10-22 16:35:11,047] [DEBUG] [axolotl.loaders.model.log_gpu_memory_usage:127] [PID:2199] Memory usage after model load 11.676GB (+11.676GB allocated, +13.172GB reserved)
165
+ trainable params: 20,185,088 || all params: 7,635,801,600 || trainable%: 0.2643
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+ [2025-10-22 16:35:11,254] [DEBUG] [axolotl.loaders.model.log_gpu_memory_usage:127] [PID:2199] after adapters 8.565GB (+8.565GB allocated, +13.248GB reserved)
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+ [2025-10-22 16:35:16,678] [INFO] [axolotl.train.save_initial_configs:398] [PID:2199] Pre-saving adapter config to ./outputs/thoth_text_v2...
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+ [2025-10-22 16:35:16,788] [INFO] [axolotl.train.save_initial_configs:407] [PID:2199] Pre-saving model config to ./outputs/thoth_text_v2...
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+ [2025-10-22 16:35:16,790] [INFO] [axolotl.train.execute_training:196] [PID:2199] Starting trainer...
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  0%| | 0/1 [00:00<?, ?it/s][2025-10-22 16:35:17,741] [WARNING] [py.warnings._showwarnmsg:110] [PID:2199] /root/miniconda3/envs/py3.11/lib/python3.11/site-packages/bitsandbytes/autograd/_functions.py:186: UserWarning: MatMul8bitLt: inputs will be cast from torch.bfloat16 to float16 during quantization
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+ [2025-10-22 16:35:18,999] [INFO] [axolotl.train.save_trained_model:218] [PID:2199] Training completed! Saving trained model to ./outputs/thoth_text_v2.
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+ [2025-10-22 16:35:19,335] [INFO] [axolotl.train.save_trained_model:336] [PID:2199] Model successfully saved to ./outputs/thoth_text_v2
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