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Training in progress, epoch 1

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README.md ADDED
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+ ---
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+ base_model: microsoft/phi-2
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+ library_name: transformers
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+ model_name: phi-2-sft
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+ tags:
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+ - generated_from_trainer
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+ - trl
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+ - sft
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+ licence: license
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+ ---
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+
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+ # Model Card for phi-2-sft
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+
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+ This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2).
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+ It has been trained using [TRL](https://github.com/huggingface/trl).
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+
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+ ## Quick start
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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+ generator = pipeline("text-generation", model="NLP-Final-Project/phi-2-sft", device="cuda")
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+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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+ print(output["generated_text"])
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+ ```
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+
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+ ## Training procedure
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+
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+
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+
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+
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+
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+ This model was trained with SFT.
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+
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+ ### Framework versions
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+
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+ - TRL: 1.3.0
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+ - Transformers: 5.7.0
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+ - Pytorch: 2.11.0
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+ - Datasets: 4.8.5
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+ - Tokenizers: 0.22.2
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+
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+ ## Citations
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+
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+
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+
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+ Cite TRL as:
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+
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+ ```bibtex
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+ @software{vonwerra2020trl,
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+ title = {{TRL: Transformers Reinforcement Learning}},
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+ author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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+ license = {Apache-2.0},
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+ url = {https://github.com/huggingface/trl},
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+ year = {2020}
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+ }
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+ ```
config.json ADDED
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+ {
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+ "architectures": [
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+ "PhiForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 50256,
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+ "dtype": "bfloat16",
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+ "embd_pdrop": 0.0,
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+ "eos_token_id": 50256,
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+ "hidden_act": "gelu_new",
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+ "hidden_size": 2560,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 10240,
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 2048,
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+ "model_type": "phi",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 32,
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+ "pad_token_id": 50256,
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+ "partial_rotary_factor": 0.4,
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+ "qk_layernorm": false,
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+ "resid_pdrop": 0.1,
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+ "rope_parameters": {
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+ "partial_rotary_factor": 0.4,
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+ "rope_theta": 10000.0,
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+ "rope_type": "default"
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+ },
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+ "tie_word_embeddings": false,
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+ "transformers_version": "5.7.0",
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+ "use_cache": false,
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+ "vocab_size": 51200
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+ }
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+ {
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+ "transformers_version": "5.7.0"
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+ "clean_up_tokenization_spaces": true,
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