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Browse files- README.md +69 -0
- adapter_model.safetensors +1 -1
README.md
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---
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base_model: meta-llama/Meta-Llama-3-8B
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datasets:
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- generator
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library_name: peft
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license: llama3
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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: NEW-Meta-Llama-3-8B-MEDAL-flash-attention-2-cosine-evaldata
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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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# NEW-Meta-Llama-3-8B-MEDAL-flash-attention-2-cosine-evaldata
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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 generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.4725
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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: 0.0005
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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: 4
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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: 0.03
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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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| 2.5114 | 0.0164 | 100 | 2.4076 |
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| 2.4269 | 0.0327 | 200 | 2.4570 |
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| 2.4619 | 0.0491 | 300 | 2.4668 |
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| 2.4684 | 0.0654 | 400 | 2.4725 |
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 1342239008
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version https://git-lfs.github.com/spec/v1
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size 1342239008
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