71 lines
1.7 KiB
Markdown
71 lines
1.7 KiB
Markdown
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---
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library_name: transformers
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license: llama3
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base_model: meta-llama/Meta-Llama-3-8B
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tags:
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- alignment-handbook
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- generated_from_trainer
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datasets:
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- HuggingFaceH4/ultrachat_200k
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model-index:
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- name: llama-3-8b-base-ultrachat-sft-4xh100
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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-3-8b-base-ultrachat-sft-4xh100
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the HuggingFaceH4/ultrachat_200k dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0704
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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: 4
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 128
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- total_eval_batch_size: 8
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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: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.1457 | 0.2138 | 200 | 1.1342 |
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| 1.0927 | 0.4276 | 400 | 1.1092 |
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| 1.0811 | 0.6414 | 600 | 1.0847 |
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| 1.0531 | 0.8552 | 800 | 1.0704 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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