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Model: Shekswess/trlm-stage-2-sft-final-2 Source: Original Platform
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: Shekswess/trlm-stage-1-sft-final-2
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tags:
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- trl
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- sft
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- reasoning
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- generated_from_trainer
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model-index:
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- name: trlm-stage-2-sft-final-2
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results: []
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---
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# 🧠 trlm-stage-2-sft-final-2
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`trlm-stage-2-sft-final-2` is the **Stage 2** post-training model for the **Tiny Reasoning Language Model (trlm)** project.
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This stage focuses on **reasoning tasks**, fine-tuned on a curated dataset of **78,000 entries** with reasoning tokens (`<think>...</think>`).
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---
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## 📖 Model Description
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- **Base Model**: [Shekswess/trlm-stage-1-sft-final-2](https://huggingface.co/Shekswess/trlm-stage-1-sft-final-2)
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- **Type**: Causal Language Model (decoder-only transformer)
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- **Stage**: Post-training **Stage 2 (SFT)**
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- **Objective**: Equip the model with **reasoning ability**, multi-turn thought structuring, and explicit `<think>` chain-of-thought representations.
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This stage teaches the model to **analyze problems step-by-step, reason with intermediate thoughts, and provide structured answers**.
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---
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## 🎯 Intended Uses & Limitations
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### Intended Uses
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- Reasoning-based question answering
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- Step-by-step logical explanations
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- Multi-turn reasoning with `<think>` traces
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- Precursor to preference optimization (Stage 3)
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### Limitations
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- May overfit on reasoning style and hallucinate `<think>` tokens in simple tasks
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- Still limited in knowledge scope (135M parameters)
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- Trained only on English datasets
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---
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## 📊 Training Data
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This model was trained on the dataset:
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👉 [**Shekswess/trlm-sft-stage-2-final-2**](https://huggingface.co/datasets/Shekswess/trlm-sft-stage-2-final-2)
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**Dataset summary**:
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- **Entries**: 78,000
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- **Sources**: 6 HuggingFaceTB/smoltalk2 subsets
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- **Focus**: Reasoning tasks with `<think>` annotations
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| Source Dataset | Entries | Percentage % |
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|----------------|---------|---|
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| Llama_Nemotron_Post_Training_Dataset_reasoning_r1 | 40,200 | 51.5% |
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| OpenThoughts3_1.2M | 20,000 | 25.6% |
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| multi_turn_reasoning_if_think | 10,000 | 12.8% |
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| aya_dataset_Qwen3_32B_think | 5,000 | 6.4% |
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| smoltalk_everyday_convs_reasoning_Qwen3_32B_think | 2,000 | 2.6% |
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| s1k_1.1_think | 800 | 1.0% |
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---
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## ⚙️ Training Procedure
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### Training Hyperparameters
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- **Learning rate**: 3e-4
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- **Train batch size**: 32
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- **Eval batch size**: 8
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- **Gradient accumulation steps**: 4
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- **Total effective batch size**: 128
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- **Optimizer**: AdamW (betas=(0.9, 0.99), eps=1e-08)
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- **LR Scheduler**: Cosine with warmup ratio 0.1
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- **Epochs**: 1
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- **Seed**: 42
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### Framework Versions
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- **Transformers**: 4.56.2
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- **PyTorch**: 2.7.1+rocm7.0.0.git698b58a9
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- **Datasets**: 4.0.0
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- **Tokenizers**: 0.22.1
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---
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## 🚀 Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_name = "Shekswess/trlm-stage-2-sft-final-2"
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# Load tokenizer & model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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# Example inference with reasoning
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messages = [
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{"role": "user", "content": "If a train travels 60 km in 1 hour and another 90 km in 1.5 hours, what is the average speed?"}
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]
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# Apply chat template
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text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer([text], return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=256)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## 📌 Next Steps
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- **Stage 3**: DPO / preference optimization for reasoning stability
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---
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Part of the Tiny Reasoning Language Model (trlm) post-training pipeline.
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{% for message in messages %}
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{% if loop.first and messages[0]['role'] != 'system' %}
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{{ '<|im_start|>system\nYou are a helpful AI assistant named Tiny Reasoning Language Model, trained by Shekswess. You are an assistant, with the ability to do reasoning. When performing reasoning always perform your full chain of thought inside <think>...</think> before giving a final answer.<|im_end|>\n' }}
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{% endif %}
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{{ '<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>\n' }}
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{% endfor %}
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{% if add_generation_prompt %}
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{{ '<|im_start|>assistant\n' }}
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{% endif %}
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config.json
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"architectures": [
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|
||||
"pad_token": "<|im_end|>",
|
||||
"tokenizer_class": "GPT2Tokenizer",
|
||||
"unk_token": "<|endoftext|>",
|
||||
"vocab_size": 49152
|
||||
}
|
||||
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:a3e22f98d728e7421f01c5d56d01d6bb1c5abbed0477f55b7b6f41c22db96054
|
||||
size 6225
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user