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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - Intel/orca_dpo_pairs
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+ - mlabonne/chatml_dpo_pairs
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+ language:
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+ - en
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+ library_name: transformers
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+ ---
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+ More information about previous [Neuronovo/neuronovo-7B-v0.2](https://huggingface.co/Neuronovo/neuronovo-7B-v0.2) version available here: 🔗[Don't stop DPOptimizing!](https://www.linkedin.com/pulse/dont-stop-dpoptimizing-jan-koco%2525C5%252584-mq4qf)
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+
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+ Author: Jan Kocoń     🔗[LinkedIn](https://www.linkedin.com/in/jankocon/)     🔗[Google Scholar](https://scholar.google.com/citations?user=pmQHb5IAAAAJ&hl=en&oi=ao)     🔗[ResearchGate](https://www.researchgate.net/profile/Jan-Kocon-2)
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+
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+ Changes concerning [Neuronovo/neuronovo-7B-v0.2](https://huggingface.co/Neuronovo/neuronovo-7B-v0.2):
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+
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+ 1. **Training Dataset**: In addition to the [Intel/orca_dpo_pairs](Intel/orca_dpo_pairs) dataset, this version incorporates a [mlabonne/chatml_dpo_pairs](https://huggingface.co/datasets/mlabonne/chatml_dpo_pairs). The combined datasets enhance the model's capabilities in dialogues and interactive scenarios, further specializing it in natural language understanding and response generation.
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+
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+ 2. **Tokenizer and Formatting**: The tokenizer now originates directly from the [Neuronovo/neuronovo-7B-v0.2](https://huggingface.co/Neuronovo/neuronovo-7B-v0.2) model.
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+
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+ 3. **Training Configuration**: The training approach has shifted from using `max_steps=200` to `num_train_epochs=1`. This represents a change in the training strategy, focusing on epoch-based training rather than a fixed number of steps.
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+
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+ 4. **Learning Rate**: The learning rate has been reduced to a smaller value of `5e-6`. This finer learning rate allows for more precise adjustments during the training process, potentially leading to better model performance.
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+ {
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+ "model_type": "mistral",
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+ "num_hidden_layers": 40,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.36.2",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
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tokenizer_config.json ADDED
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+ {
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+ "tokenizer_class": "LlamaTokenizer",
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+ }