Update README.md

README.md

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-# Model Card for nasa-smd-ibm-distil-v0.1 (INDUS-Small)
+# Model Card for INDUS-Small (nasa-smd-ibm-distil-v0.1)
 
-nasa-smd-ibm-distil-v0.1 (INDUS-Small) is a distilled version of the RoBERTa-based, Encoder-only transformer model Indus (nasa-impact/nasa-smd-ibm-v0.1), domain-adapted for NASA Science Mission Directorate (SMD) applications. It's fine-tuned on scientific journals and articles relevant to NASA SMD, aiming to enhance natural language technologies like information retrieval and intelligent search.
+INDUS-Small(nasa-smd-ibm-distil-v0.1) is a distilled version of the RoBERTa-based, Encoder-only transformer model INDUS (nasa-impact/nasa-smd-ibm-v0.1), domain-adapted for NASA Science Mission Directorate (SMD) applications. It's fine-tuned on scientific journals and articles relevant to NASA SMD, aiming to enhance natural language technologies like information retrieval and intelligent search.
 
 We trained the smaller model, INDUS_SMALL, with 38M parameters through knowledge distillation techniques by using INDUS as the teacher. INDUS_SMALL follows a 4-layer architecture recommended by the Neural Architecture Search engine (Trivedi et al., 2023) with an optimal trade-off between performance and latency. We adopted the distillation objective proposed in MiniLMv2 (Wang et al., 2021) to transfer fine-grained self-attention relations, which has been shown to be the current state-of-the-art (Udagawa et al., 2023). Using this objective, we trained the model for 500K steps with an effective batch size of 480 on 30 V100 GPUs.
 
 ## Model Details
-- **Base Model**: RoBERTa
+- **Base Model**: INDUS
 - **Tokenizer**: Custom
 - **Original version Parameters**: 125M
 - **Pretraining Strategy**: Masked Language Modeling (MLM)