artificialguybr
/

Meta-Llama-3.1-8B-openhermes-2.5

@@ -1,199 +1,102 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 ---
+tags:
+  - llama
+  - instruct
+  - finetune
+  - chatml
+  - gpt4
+  - synthetic data
+  - distillation
+model-index:
+  - name: Meta-Llama-3.1-8B-openhermes-2.5
+    results: []
+license: apache-2.0
+language:
+  - en
 library_name: transformers
+datasets:
+- teknium/OpenHermes-2.5
 ---
+# Model Card for Meta-Llama-3.1-8B-openhermes-2.5
+This model is a fine-tuned version of Meta-Llama-3.1-8B on the OpenHermes-2.5 dataset.
 ## Model Details
 ### Model Description
+This is a fine-tuned version of the Meta-Llama-3.1-8B model, trained on the OpenHermes-2.5 dataset. It is designed for instruction following and general language tasks.
+- **Developed by:** artificialguybr
+- **Model type:** Causal Language Model
+- **Language(s):** English
+- **License:** apache-2.0
+- **Finetuned from model:** meta-llama/Meta-Llama-3.1-8B
+### Model Sources
+- **Repository:** https://huggingface.co/artificialguybr/Meta-Llama-3.1-8B-openhermes-2.5
 ## Uses
+This model can be used for various natural language processing tasks, particularly those involving instruction following and general language understanding.
 ### Direct Use
+The model can be used for tasks such as text generation, question answering, and other language-related applications.
 ### Out-of-Scope Use
+The model should not be used for generating harmful or biased content. Users should be aware of potential biases in the training data.
 ## Training Details
 ### Training Data
+The model was fine-tuned on the teknium/OpenHermes-2.5 dataset.
 ### Training Procedure
 #### Training Hyperparameters
+- **Training regime:** BF16 mixed precision
+- **Optimizer:** AdamW
+- **Learning rate:** Started at 0.00000249316296439037 (decaying)
+- **Batch size:** Not specified (gradient accumulation steps: 8)
+- **Training steps:** 13,368
+- **Evaluation strategy:** Steps (every 0.16666666666666666 steps)
+- **Gradient checkpointing:** Enabled
+- **Weight decay:** 0
+#### Hardware and Software
+- **Hardware:** NVIDIA A100-SXM4-80GB (1 GPU)
+- **Software Framework:** 🤗 Transformers, Axolotl
 ## Evaluation
+### Metrics
+- **Loss:** 0.6727465987205505 (evaluation)
+- **Perplexity:** Not provided
 ### Results
+- **Evaluation runtime:** 2,676.4173 seconds
+- **Samples per second:** 18.711
+- **Steps per second:** 18.711
+## Model Architecture
+- **Model Type:** LlamaForCausalLM
+- **Hidden size:** 4,096
+- **Intermediate size:** 14,336
+- **Number of attention heads:** Not specified
+- **Number of layers:** Not specified
+- **Activation function:** SiLU
+- **Vocabulary size:** 128,256
+## Limitations and Biases
+More information is needed about specific limitations and biases of this model.