rbelanec/train_mnli_42_1779286677
The rbelanec/train_mnli_42_1779286677 model is a 1 billion parameter language model, fine-tuned from meta-llama/Llama-3.2-1B-Instruct. It has been specifically trained on the MNLI (Multi-Genre Natural Language Inference) dataset, achieving a validation loss of 0.1007. This model is optimized for natural language inference tasks, making it suitable for determining entailment, contradiction, or neutrality between text pairs.
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Model Overview
This model, rbelanec/train_mnli_42_1779286677, is a 1 billion parameter language model derived from meta-llama/Llama-3.2-1B-Instruct. It has undergone fine-tuning specifically on the MNLI (Multi-Genre Natural Language Inference) dataset.
Key Capabilities
- Natural Language Inference (NLI): The model is specialized in NLI tasks, which involve analyzing two sentences (a premise and a hypothesis) and determining their relationship: entailment, contradiction, or neutrality.
- Performance: During training, the model achieved a validation loss of 0.1007, indicating its proficiency in the fine-tuned task.
Training Details
The model was trained with a learning rate of 2e-06 over 1 epoch, utilizing AdamW_TORCH optimizer and a cosine learning rate scheduler with a warmup ratio of 0.1. The training involved processing approximately 38.2 million input tokens.
Good For
- Applications requiring robust natural language inference capabilities.
- Tasks involving textual entailment recognition and semantic relationship classification between sentences.