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Phi-3-Summarization-QLoRa

Summarization
PEFT
TensorBoard
Safetensors
trl
sft
Generated from Trainer
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End of training

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Files changed (10) hide show
  1. README.md +70 -0
  2. adapter_config.json +31 -0
  3. adapter_model.safetensors +3 -0
  4. added_tokens.json +40 -0
  5. runs/Apr25_16-02-21_4827ab5657cb/events.out.tfevents.1714061023.4827ab5657cb.589.0 +3 -0
  6. special_tokens_map.json +27 -0
  7. tokenizer.json +0 -0
  8. tokenizer.model +3 -0
  9. tokenizer_config.json +349 -0
  10. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: mit
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+ library_name: peft
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+ tags:
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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ base_model: microsoft/Phi-3-mini-128k-instruct
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+ datasets:
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+ - scitldr
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+ model-index:
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+ - name: Summarization-Phi-3
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+ results: []
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+ ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Summarization-Phi-3
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+
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+ This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the scitldr dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.1554
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 1
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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: linear
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+ - num_epochs: 2
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 2.0689 | 0.2510 | 500 | 2.1439 |
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+ | 2.0455 | 0.5020 | 1000 | 2.1388 |
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+ | 2.0665 | 0.7530 | 1500 | 2.1349 |
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+ | 2.0481 | 1.0040 | 2000 | 2.1308 |
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+ | 1.9051 | 1.2550 | 2500 | 2.1573 |
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+ | 1.8524 | 1.5060 | 3000 | 2.1588 |
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+ | 1.8247 | 1.7570 | 3500 | 2.1554 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.10.0
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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