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--- |
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language: en |
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license: mit |
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tags: |
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- text-classification |
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- ufc |
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- prediction |
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- sports |
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--- |
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# UFC Fight Outcome Predictor (DistilBERT-based) |
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This model is a fine-tuned BERT classifier designed to predict the **outcome of UFC fights** based on textual inputs such as pre-fight analysis, fighter stats. It is trained as a **binary text classification** model. |
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## Use Case |
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You can use this model to: |
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- Predict likely fight outcomes from textual descriptions |
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## Model Details |
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- **Base model**: `bert-base-uncased` |
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- **Task**: Binary text classification (Win / Loss) |
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- **Training data**: Custom UFC-related dataset |
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- **Input**: Text (e.g., fighter matchups, stats) |
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- **Output**: Binary class prediction (`0 = Fighter B wins`, `1 = Fighter A wins`) |
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## Example Usage (Python) |
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```python |
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from transformers import DistilBertForSequenceClassification, DistilBertTokenizer |
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loaded_model = DistilBertForSequenceClassification.from_pretrained("/content/fine_tuned_ufc_model") |
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loaded_tokenizer = DistilBertTokenizer.from_pretrained("/content/fine_tuned_ufc_model") |
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def predict_winner(fighter_a_stats, fighter_b_stats, model, tokenizer): |
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input_text = ( |
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f"Fighter A: {fighter_a_stats} || Fighter B: {fighter_b_stats}" |
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) |
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inputs = tokenizer(input_text, return_tensors="pt", truncation=True, padding=True).to(device) |
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outputs = model(**inputs) |
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probs = torch.nn.functional.softmax(outputs.logits, dim=-1) |
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pred = torch.argmax(probs, dim=1).item() |
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return {"Fighter A wins": float(probs[0][0]), "Fighter B wins": float(probs[0][1])}, pred |
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fighter_a = "Height: 73 in | Reach: 80 in | Str. Acc: 0.57 | Str. Def: 0.58 | SLpM: 4.25 | SApM: 2.12" |
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fighter_b = "Height: 70 in | Reach: 71 in | Str. Acc: 0.49 | Str. Def: 0.55 | SLpM: 4.00 | SApM: 3.00" |
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probs, winner = predict_winner(fighter_a, fighter_b, loaded_model, loaded_tokenizer) |
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print(probs, "Winner Label (0=A, 1=B):", winner) |
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// Example Output: {'Fighter A wins': 0.03644789755344391, 'Fighter B wins': 0.9635520577430725} Winner Label (0=A, 1=B): 1 |
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``` |
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## Files |
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- model.safetensors: The model weights in safetensors format |
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- config.json: Model architecture config |
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- tokenizer_config.json, special_tokens_map.json, vocab.txt: Tokenizer files |
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✍️ Author |
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Created by @Ishwak1 |
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### For questions or fine-tuning on your own fight data, feel free to open a discussion! |
