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--- |
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library_name: transformers |
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license: other |
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base_model: instruction-pretrain/finance-Llama3-8B |
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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: pretrain_sft_finance |
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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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# pretrain_sft_finance |
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This model is a fine-tuned version of [instruction-pretrain/finance-Llama3-8B](https://huggingface.co/instruction-pretrain/finance-Llama3-8B) on the time_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2738 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 16 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 4.1092 | 0.0649 | 10 | 4.4912 | |
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| 2.1524 | 0.1299 | 20 | 1.8664 | |
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| 0.7796 | 0.1948 | 30 | 0.6781 | |
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| 0.3127 | 0.2597 | 40 | 0.2871 | |
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| 0.4223 | 0.3247 | 50 | 0.2762 | |
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| 0.2854 | 0.3896 | 60 | 0.2877 | |
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| 0.2908 | 0.4545 | 70 | 0.3328 | |
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| 0.4468 | 0.5195 | 80 | 0.3878 | |
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| 0.2962 | 0.5844 | 90 | 0.2747 | |
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| 0.2759 | 0.6494 | 100 | 0.2835 | |
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| 0.3065 | 0.7143 | 110 | 0.2901 | |
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| 0.2882 | 0.7792 | 120 | 0.2735 | |
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| 0.2945 | 0.8442 | 130 | 0.2920 | |
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| 0.2805 | 0.9091 | 140 | 0.2734 | |
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| 0.2696 | 0.9740 | 150 | 0.2738 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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