Falcon-RW-1B Fine-tuned with LoRA on IMDb Sentiment Dataset
This is a Falcon-RW-1B language model fine-tuned using LoRA (Low-Rank Adaptation) for causal language modeling, trained on a subset of the IMDb movie reviews dataset for sentiment-related text generation tasks.
Model Details
Model Description
This model is based on the Falcon-RW-1B pretrained causal language model, fine-tuned with parameter-efficient LoRA adapters targeting the "query_key_value" modules. Training was performed on a small subset of the IMDb dataset (1,000 samples) with sequences truncated/padded to 128 tokens.
This model can be used for generating or completing English text sequences related to movie reviews, sentiment analysis prompts, or similar NLP causal language modeling tasks.
Downstream Use
The LoRA adapters allow further parameter-efficient fine-tuning for other NLP tasks or domain adaptation, leveraging the Falcon-RW-1B base.
Out-of-Scope Use
This model is not optimized for zero-shot classification or tasks outside of causal language modeling.
Not suitable for languages other than English.
The small training subset limits generalization; performance on real-world text may vary.
Bias, Risks, and Limitations
The base Falcon-RW-1B model inherits biases present in the pretraining data.
The fine-tuning on IMDb is limited in scope and size; results may be biased toward movie review sentiment.
Use caution when deploying in production or sensitive applications.
