Vidyuth commited on
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Training complete

Browse files
README.md CHANGED
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  ---
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- license: apache-2.0
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- base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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  tags:
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  - generated_from_trainer
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  model-index:
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  - name: results
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  results: []
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -13,7 +13,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # results
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- This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on an unknown dataset.
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  ## Model description
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@@ -29,25 +29,36 @@ More information needed
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  ## Training procedure
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0004
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- - train_batch_size: 4
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  - eval_batch_size: 8
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  - seed: 42
 
 
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.03
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- - num_epochs: 4
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-
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- ### Training results
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-
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-
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  ### Framework versions
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- - Transformers 4.31.0
 
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.17.0
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- - Tokenizers 0.13.3
 
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  ---
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+ base_model: jianghc/medical_chatbot
 
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  tags:
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  - generated_from_trainer
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  model-index:
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  - name: results
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  results: []
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+ library_name: peft
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # results
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+ This model is a fine-tuned version of [jianghc/medical_chatbot](https://huggingface.co/jianghc/medical_chatbot) on an unknown dataset.
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  ## Model description
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  ## Training procedure
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+
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+ The following `bitsandbytes` quantization config was used during training:
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+ - quant_method: bitsandbytes
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+ - load_in_8bit: False
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+ - load_in_4bit: True
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+ - llm_int8_threshold: 6.0
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+ - llm_int8_skip_modules: None
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+ - llm_int8_enable_fp32_cpu_offload: False
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+ - llm_int8_has_fp16_weight: False
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+ - bnb_4bit_quant_type: nf4
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+ - bnb_4bit_use_double_quant: False
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+ - bnb_4bit_compute_dtype: float16
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 1
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  - eval_batch_size: 8
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  - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 4
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: constant
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  - lr_scheduler_warmup_ratio: 0.03
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+ - training_steps: 10000
 
 
 
 
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  ### Framework versions
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+ - PEFT 0.4.0
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+ - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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