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--- |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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library_name: peft |
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license: llama3.1 |
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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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model-index: |
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- name: Llama-31-8B_task-3_120-samples_config-2 |
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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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# Llama-31-8B_task-3_120-samples_config-2 |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8608 |
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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: 0.0001 |
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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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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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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: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 2.4469 | 0.9091 | 5 | 2.3539 | |
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| 1.8346 | 2.0 | 11 | 1.4922 | |
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| 0.7576 | 2.9091 | 16 | 0.7652 | |
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| 0.6409 | 4.0 | 22 | 0.5627 | |
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| 0.4304 | 4.9091 | 27 | 0.5238 | |
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| 0.3624 | 6.0 | 33 | 0.4705 | |
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| 0.3967 | 6.9091 | 38 | 0.4452 | |
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| 0.3293 | 8.0 | 44 | 0.4328 | |
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| 0.2432 | 8.9091 | 49 | 0.4302 | |
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| 0.2102 | 10.0 | 55 | 0.4359 | |
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| 0.2004 | 10.9091 | 60 | 0.4583 | |
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| 0.1634 | 12.0 | 66 | 0.4724 | |
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| 0.1177 | 12.9091 | 71 | 0.5530 | |
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| 0.0376 | 14.0 | 77 | 0.7361 | |
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| 0.0204 | 14.9091 | 82 | 0.7768 | |
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| 0.0118 | 16.0 | 88 | 0.8608 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
