57 lines
1.4 KiB
Markdown
57 lines
1.4 KiB
Markdown
---
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license: apache-2.0
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base_model: Mostafa8Mehrabi/qwen3-50m-fp16
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tags:
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- qwen
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- c4
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- pretrained
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- fp16
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- notebook
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library_name: transformers
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pipeline_tag: text-generation
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---
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# 🚀 Qwen3-50M C4 Pretrained (FP16) - Notebook Version
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Pretrained Qwen3-50M model on C4 dataset using FP16 precision in notebook environment.
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## 📊 Training Results
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- **Final Training Loss**: 4.0267
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- **Final Validation Loss**: 4.120617866516113
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- **Training Samples**: 1,000,000
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- **Epochs**: 3
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- **Precision**: FP16
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## 🚀 Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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tokenizer = AutoTokenizer.from_pretrained("Mostafa8Mehrabi/qwen3-50m-c4-final")
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model = AutoModelForCausalLM.from_pretrained(
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"Mostafa8Mehrabi/qwen3-50m-c4-final",
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torch_dtype=torch.float16,
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device_map="auto"
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)
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# Generate text
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prompt = "The future of artificial intelligence is"
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=100, do_sample=True)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## 📁 Checkpoints
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Training checkpoints (also in FP16) are available at: Mostafa8Mehrabi/qwen3-50m-c4-checkpoints
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## 🔧 Training Environment
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This model was trained in a notebook environment with the following configuration:
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- Batch Size: 128
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- Learning Rate: 5e-05
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- Max Length: 512
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- Number of Processes: 8
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