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--- |
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license: other |
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base_model: meta-llama/Meta-Llama-3-70B |
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tags: |
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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: C013_Meta-Llama-3-70B_pretrain_20240508_200642 |
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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 |
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should probably proofread and complete it, then remove this comment. --> |
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# C013_Meta-Llama-3-70B_pretrain_20240508_200642 |
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This model is a fine-tuned version of [/mnt/fl/models/llama3/Meta-Llama-3-70B](https://huggingface.co//mnt/fl/models/llama3/Meta-Llama-3-70B) on the C013_data dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7400 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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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: 3e-06 |
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- train_batch_size: 2 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 32 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_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: polynomial |
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- lr_scheduler_warmup_ratio: 0.075 |
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- num_epochs: 4.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.8776 | 0.2090 | 7 | 0.7902 | |
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| 0.8473 | 0.4179 | 14 | 0.7703 | |
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| 0.8293 | 0.6269 | 21 | 0.7603 | |
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| 0.8173 | 0.8358 | 28 | 0.7481 | |
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| 0.7415 | 1.0448 | 35 | 0.7402 | |
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| 0.6794 | 1.2537 | 42 | 0.7419 | |
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| 0.6688 | 1.4627 | 49 | 0.7392 | |
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| 0.6498 | 1.6716 | 56 | 0.7367 | |
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| 0.6701 | 1.8806 | 63 | 0.7358 | |
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| 0.664 | 2.0896 | 70 | 0.7355 | |
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| 0.6447 | 2.2985 | 77 | 0.7361 | |
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| 0.6412 | 2.5075 | 84 | 0.7373 | |
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| 0.6458 | 2.7164 | 91 | 0.7383 | |
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| 0.6356 | 2.9254 | 98 | 0.7387 | |
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| 0.6398 | 3.1343 | 105 | 0.7387 | |
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| 0.6228 | 3.3433 | 112 | 0.7391 | |
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| 0.6139 | 3.5522 | 119 | 0.7395 | |
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| 0.591 | 3.7612 | 126 | 0.7398 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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