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Litzy619
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Va0309B1

Safetensors
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Files changed (10) hide show
  1. README.md +95 -0
  2. adapter_config.json +20 -0
  3. adapter_model.bin +3 -0
  4. added_tokens.json +40 -0
  5. merges.txt +0 -0
  6. model.safetensors +3 -0
  7. special_tokens_map.json +24 -0
  8. tokenizer_config.json +328 -0
  9. training_args.bin +3 -0
  10. vocab.json +0 -0
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: microsoft/phi-2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: Va0309B1
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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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+ # Va0309B1
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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) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0706
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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: 3e-05
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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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+ - gradient_accumulation_steps: 32
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine_with_restarts
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+ - lr_scheduler_warmup_steps: 20
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+ - num_epochs: 3
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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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+ | 2.7676 | 0.09 | 10 | 2.7256 |
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+ | 2.6283 | 0.17 | 20 | 2.4272 |
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+ | 2.2188 | 0.26 | 30 | 1.8633 |
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+ | 1.6664 | 0.34 | 40 | 1.3024 |
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+ | 1.1333 | 0.43 | 50 | 0.7344 |
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+ | 0.5536 | 0.51 | 60 | 0.2242 |
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+ | 0.1952 | 0.6 | 70 | 0.1010 |
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+ | 0.1271 | 0.68 | 80 | 0.0909 |
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+ | 0.1187 | 0.77 | 90 | 0.0872 |
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+ | 0.1194 | 0.85 | 100 | 0.0851 |
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+ | 0.1135 | 0.94 | 110 | 0.0831 |
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+ | 0.1119 | 1.02 | 120 | 0.0805 |
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+ | 0.1132 | 1.11 | 130 | 0.0794 |
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+ | 0.1036 | 1.19 | 140 | 0.0790 |
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+ | 0.1083 | 1.28 | 150 | 0.0780 |
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+ | 0.1063 | 1.37 | 160 | 0.0765 |
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+ | 0.1087 | 1.45 | 170 | 0.0756 |
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+ | 0.0969 | 1.54 | 180 | 0.0740 |
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+ | 0.1024 | 1.62 | 190 | 0.0738 |
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+ | 0.1044 | 1.71 | 200 | 0.0727 |
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+ | 0.1013 | 1.79 | 210 | 0.0728 |
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+ | 0.0985 | 1.88 | 220 | 0.0724 |
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+ | 0.0961 | 1.96 | 230 | 0.0714 |
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+ | 0.1015 | 2.05 | 240 | 0.0717 |
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+ | 0.096 | 2.13 | 250 | 0.0710 |
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+ | 0.0935 | 2.22 | 260 | 0.0709 |
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+ | 0.0913 | 2.3 | 270 | 0.0709 |
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+ | 0.1026 | 2.39 | 280 | 0.0706 |
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+ | 0.0965 | 2.47 | 290 | 0.0705 |
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+ | 0.1029 | 2.56 | 300 | 0.0710 |
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+ | 0.0961 | 2.65 | 310 | 0.0702 |
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+ | 0.0991 | 2.73 | 320 | 0.0704 |
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+ | 0.0985 | 2.82 | 330 | 0.0705 |
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+ | 0.0929 | 2.9 | 340 | 0.0703 |
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+ | 0.0948 | 2.99 | 350 | 0.0706 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0.dev0
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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