sweatSmile/marx-opt350m-finetuned-v1

🧠 Model: marx-opt350m-finetuned-v1

This is a fine-tuned version of facebook/opt-350m on the sweatSmile/marx-dataset — a conversational dataset consisting of question-answer dialogues about Marxist theory, history, and related political contexts.

The model is optimized for dialogue-style QA on political/philosophical topics.

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📊 Training Details

• Base model: facebook/opt-350m
• Dataset: sweatSmile/marx-dataset
• Epochs: 5
• Trainer: TRL's SFTTrainer from trl
• Loss: Reduced steadily to ~0.36
• ROUGE-L: ~0.53 on evaluation set

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🔍 Example Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("sweatSmile/marx-opt350m-finetuned-v1")
tokenizer = AutoTokenizer.from_pretrained("sweatSmile/marx-opt350m-finetuned-v1")

prompt = "### Human: Who were commissioned to prepare the party programme for the Communist League?\n### Assistant:"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))