added model card

README.md

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-license: mit
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+---
+license: mit
+---
+### Model Card: **TinyLlama-1.1B-Chat-v1.0-Unfiltered**
+
+---
+
+**Model Name**: TinyLlama-1.1B-Chat-v1.0-Unfiltered  
+**Model Type**: Conversational AI Model  
+**Architecture**: Based on a 1.1B parameter TinyLlama architecture  
+
+**Training Data**:  
+- Fine-tuned on the "dan_remixed" dataset (2.7MB).  
+- The dataset improves spelling, grammar, and consistency while replacing references to violent crimes with non-violent activities and removes self-censorship from explicatives.
+
+**Training Time**: Approximately 30-45 minutes. Each validation epoch takes ~322 seconds.  
+**Hardware**: Trained on GPU (specific GPU details not provided).
+
+---
+
+**Training Performance**:
+- **Epoch Losses**:
+  - Epoch 1: 0.7209
+  - Epoch 2: 0.4441
+  - Epoch 3: 0.3683
+  - Epoch 4: 0.3358
+  - Epoch 5: 0.3145
+- **Final Training Loss (Epoch 5)**: 0.3145
+
+---
+
+**Validation Performance** (5 Epochs):  
+- **Epoch 1**:  
+  - Training Loss: 0.2921  
+  - Validation Loss: 0.7962  
+  - Perplexity: 2.22  
+  - Epoch completed in 321.64 seconds  
+
+- **Epoch 2**:  
+  - Training Loss: 0.2872  
+  - Validation Loss: 0.7672  
+  - Perplexity: 2.15  
+  - Epoch completed in 321.91 seconds  
+
+- **Epoch 3**:  
+  - Training Loss: 0.2874  
+  - Validation Loss: 0.7821  
+  - Perplexity: 2.19  
+  - Epoch completed in 321.94 seconds  
+
+- **Epoch 4**:  
+  - Training Loss: 0.2864  
+  - Validation Loss: 0.7796  
+  - Perplexity: 2.18  
+  - Epoch completed in 322.01 seconds  
+
+- **Epoch 5**:  
+  - Training Loss: 0.2831  
+  - Validation Loss: 0.8017  
+  - Perplexity: 2.23  
+  - Epoch completed in 322.01 seconds
+
+---
+
+**Optimizer**: AdamW, learning rate: 1e-5  
+**Loss Function**: Cross-Entropy Loss, ignoring padding tokens (ignore_index=-100)  
+**Use Case**: Conversational AI designed for general, unrestricted conversation, with no filtering on the nature of responses, provided the content is non-violent.
+
+---
+
+**Limitations**:
+- Due to the small fine-tuning dataset size (2.7MB), the model may be prone to **overfitting** and **bias**.
+- The dataset has been modified to avoid violent language, but the model might still exhibit strong or explicit responses.
+
+**Metrics**:
+- Loss and perplexity have been tracked, and more conversational metrics (like BLEU, ROUGE, or human evaluation) could be explored.
+