Model save
Browse files- README.md +69 -0
- all_results.json +9 -0
- train_results.json +9 -0
- trainer_state.json +260 -0
README.md
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---
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library_name: peft
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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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- trl
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- sft
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- generated_from_trainer
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datasets:
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- generator
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model-index:
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- name: llama3-8b-pissa-summarization-11-v1
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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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# llama3-8b-pissa-summarization-11-v1
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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: 2.3924
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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: 0.0002
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- train_batch_size: 12
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- eval_batch_size: 12
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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: 2
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- total_train_batch_size: 192
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- total_eval_batch_size: 96
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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
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.632 | 0.9966 | 148 | 2.3924 |
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### Framework versions
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- PEFT 0.13.2
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- Transformers 4.46.3
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- Pytorch 2.3.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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all_results.json
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{
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"total_flos": 6.55432743055786e+17,
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"train_loss": 1.752148318935085,
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"train_runtime": 587.2689,
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"train_samples": 129221,
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"train_samples_per_second": 48.443,
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"train_steps_per_second": 0.252
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}
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train_results.json
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"train_steps_per_second": 0.252
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}
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trainer_state.json
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