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Improve language tag (#1)

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- Improve language tag (6ddb2ce0ce618e54db5231c5ed11492184d75aaf)


Co-authored-by: Loïck BOURDOIS <[email protected]>

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  1. README.md +90 -76
README.md CHANGED
@@ -1,77 +1,91 @@
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- ---
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- library_name: transformers
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- tags:
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- - qwen2
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- - orpo
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- - unsloth
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- - philosophical
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- - esoteric
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- - multilingual
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- base_model:
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- - Qwen/Qwen2.5-7B-Instruct
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- ---
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-
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- # Model Card for forerunner-qwen7b-orpo
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-
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- <img src="https://huggingface.co/radm/forerunner-qwen7b-orpo/resolve/main/model-image.png" alt="Model Image" width="100%">
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-
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- ## Model Details
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-
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- ### Model Description
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-
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- This model is a fine-tuned version of `Qwen/Qwen2.5-7B-Instruct` using the ORPO algorithm with Unsloth for optimization. It has been trained on a custom dataset with a focus on philosophical and esoteric topics. The model is multilingual.
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-
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- - **Developed by:** radm
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- - **Finetuned from model:** `Qwen/Qwen2.5-7B-Instruct`
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- - **Model type:** Causal LM based on Qwen2 architecture
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- - **Language(s):** Multilingual
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- - **License:** Apache 2.0 (inherited from base model)
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-
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- ## Uses
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-
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- **Example Output (with temperature=0.6, repetition_penalty=1.15):**
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-
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- *User:* As a result of what mental process does duality appear in a person?
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-
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- *Model:* Dualistic thinking arises from the interaction between an individual and their environment. When a person's consciousness is not yet developed to a certain level, they experience the world through sensory perception. This perception leads to the formation of concepts such as "good" and "bad," "right" and "wrong." These oppositions manifest themselves in actions or emotions, leading to dualism. The mind then begins to differentiate between these opposites, creating a division into two parts: one that experiences and another that observes this experience. This observation is necessary for the development of language and thought processes, which are based on distinguishing and naming objects according to their properties. As a result, the mind learns to distinguish between things, people, events, and their qualities, forming a complex system of relationships. This process is similar to how a child learns to recognize and name objects around them. However, it's important to note that the duality formed within the mind does not necessarily reflect external reality but rather is a product of internal cognitive processes.
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-
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- ### Out-of-Scope Use
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-
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- The model is not designed for generating harmful, unethical, biased, or factually incorrect content. Performance on tasks outside its training domain (philosophical/esoteric chat) may be suboptimal.
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-
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- ## Bias, Risks, and Limitations
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-
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- The model inherits biases from its base model (`Qwen/Qwen2.5-7B-Instruct`) and the fine-tuning dataset. It may generate plausible-sounding but incorrect or nonsensical information, especially on complex topics. Its understanding is based on patterns in the data, not genuine comprehension or consciousness. Use the outputs with critical judgment.
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-
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- ## Training Details
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-
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- ### Training Data
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-
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- The model was fine-tuned using the ORPO algorithm on a custom dataset. This dataset contains pairs of preferred and rejected responses for given prompts, focusing on philosophical and esoteric themes. A small validation split (0.5%) was used.
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-
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- ### Training Procedure
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-
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- The training was performed using the `Unsloth` library integrated with `trl`'s `ORPOTrainer`.
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-
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- #### Training Hyperparameters
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-
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- - **Framework:** Unsloth + ORPO
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- - **Base Model:** `Qwen/Qwen2.5-7B-Instruct`
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- - **LoRA Configuration:**
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- - `r`: 64
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- - `lora_alpha`: 64
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- - `lora_dropout`: 0.0
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- - `bias`: "none"
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- - `target_modules`: ["q_proj", "v_proj", "k_proj", "o_proj", "gate_proj", "up_proj", "down_proj"]
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- - `use_rslora`: True
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- - **Precision:** bfloat16 mixed precision
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- - **Quantization:** Loaded in 4-bit
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- - **Optimizer:** Paged AdamW 8-bit
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- - **Learning Rate:** 1e-5
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- - **LR Scheduler:** Cosine
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- - **Warmup Steps:** 8
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- - **Batch Size (per device):** 1
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- - **Gradient Accumulation Steps:** 32 (Effective Batch Size: 32)
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- - **Max Sequence Length:** 3072
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- - **Epochs:** 1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - **ORPO Beta:** 0.1
 
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+ ---
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+ library_name: transformers
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+ tags:
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+ - qwen2
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+ - orpo
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+ - unsloth
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+ - philosophical
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+ - esoteric
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+ - multilingual
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+ base_model:
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+ - Qwen/Qwen2.5-7B-Instruct
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+ language:
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+ - zho
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+ - eng
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+ - fra
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+ - spa
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+ - por
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+ - deu
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+ - ita
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+ - rus
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+ - jpn
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+ - kor
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+ - vie
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+ - tha
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+ - ara
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+ ---
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+
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+ # Model Card for forerunner-qwen7b-orpo
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+
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+ <img src="https://huggingface.co/radm/forerunner-qwen7b-orpo/resolve/main/model-image.png" alt="Model Image" width="100%">
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ This model is a fine-tuned version of `Qwen/Qwen2.5-7B-Instruct` using the ORPO algorithm with Unsloth for optimization. It has been trained on a custom dataset with a focus on philosophical and esoteric topics. The model is multilingual.
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+
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+ - **Developed by:** radm
39
+ - **Finetuned from model:** `Qwen/Qwen2.5-7B-Instruct`
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+ - **Model type:** Causal LM based on Qwen2 architecture
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+ - **Language(s):** Multilingual
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+ - **License:** Apache 2.0 (inherited from base model)
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+
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+ ## Uses
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+
46
+ **Example Output (with temperature=0.6, repetition_penalty=1.15):**
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+
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+ *User:* As a result of what mental process does duality appear in a person?
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+
50
+ *Model:* Dualistic thinking arises from the interaction between an individual and their environment. When a person's consciousness is not yet developed to a certain level, they experience the world through sensory perception. This perception leads to the formation of concepts such as "good" and "bad," "right" and "wrong." These oppositions manifest themselves in actions or emotions, leading to dualism. The mind then begins to differentiate between these opposites, creating a division into two parts: one that experiences and another that observes this experience. This observation is necessary for the development of language and thought processes, which are based on distinguishing and naming objects according to their properties. As a result, the mind learns to distinguish between things, people, events, and their qualities, forming a complex system of relationships. This process is similar to how a child learns to recognize and name objects around them. However, it's important to note that the duality formed within the mind does not necessarily reflect external reality but rather is a product of internal cognitive processes.
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+
52
+ ### Out-of-Scope Use
53
+
54
+ The model is not designed for generating harmful, unethical, biased, or factually incorrect content. Performance on tasks outside its training domain (philosophical/esoteric chat) may be suboptimal.
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+
56
+ ## Bias, Risks, and Limitations
57
+
58
+ The model inherits biases from its base model (`Qwen/Qwen2.5-7B-Instruct`) and the fine-tuning dataset. It may generate plausible-sounding but incorrect or nonsensical information, especially on complex topics. Its understanding is based on patterns in the data, not genuine comprehension or consciousness. Use the outputs with critical judgment.
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+
60
+ ## Training Details
61
+
62
+ ### Training Data
63
+
64
+ The model was fine-tuned using the ORPO algorithm on a custom dataset. This dataset contains pairs of preferred and rejected responses for given prompts, focusing on philosophical and esoteric themes. A small validation split (0.5%) was used.
65
+
66
+ ### Training Procedure
67
+
68
+ The training was performed using the `Unsloth` library integrated with `trl`'s `ORPOTrainer`.
69
+
70
+ #### Training Hyperparameters
71
+
72
+ - **Framework:** Unsloth + ORPO
73
+ - **Base Model:** `Qwen/Qwen2.5-7B-Instruct`
74
+ - **LoRA Configuration:**
75
+ - `r`: 64
76
+ - `lora_alpha`: 64
77
+ - `lora_dropout`: 0.0
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+ - `bias`: "none"
79
+ - `target_modules`: ["q_proj", "v_proj", "k_proj", "o_proj", "gate_proj", "up_proj", "down_proj"]
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+ - `use_rslora`: True
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+ - **Precision:** bfloat16 mixed precision
82
+ - **Quantization:** Loaded in 4-bit
83
+ - **Optimizer:** Paged AdamW 8-bit
84
+ - **Learning Rate:** 1e-5
85
+ - **LR Scheduler:** Cosine
86
+ - **Warmup Steps:** 8
87
+ - **Batch Size (per device):** 1
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+ - **Gradient Accumulation Steps:** 32 (Effective Batch Size: 32)
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+ - **Max Sequence Length:** 3072
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+ - **Epochs:** 1
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  - **ORPO Beta:** 0.1