Model Overview

The rbelanec/train_cola_42_1774791067 model is a specialized 1 billion parameter language model. It is a fine-tuned variant of the meta-llama/Llama-3.2-1B-Instruct architecture, specifically adapted for linguistic tasks.

Key Capabilities

• Linguistic Acceptability: The model has been fine-tuned on the CoLA (Corpus of Linguistic Acceptability) dataset, indicating its primary strength lies in evaluating the grammatical acceptability of English sentences.
• Performance: Achieved a validation loss of 0.2517 on the evaluation set, with a total of 1,932,608 input tokens seen during training.

Training Details

The model was trained with the following key hyperparameters:

• Base Model: meta-llama/Llama-3.2-1B-Instruct
• Dataset: CoLA dataset
• Learning Rate: 5e-05
• Optimizer: ADAMW_TORCH
• Epochs: 5
• Batch Size: 8 (train and eval)

Intended Use Cases

This model is particularly suited for applications requiring an understanding of grammatical correctness and linguistic acceptability. Its fine-tuning on the CoLA dataset makes it a candidate for tasks such as:

• Grammar checking and correction.
• Evaluating sentence structures for natural language understanding systems.
• Research into linguistic phenomena related to sentence well-formedness.