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--- |
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library_name: transformers |
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license: llama3.1 |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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tags: |
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- alignment-handbook |
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- trl |
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- sft |
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- generated_from_trainer |
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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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- barc0/transduction_heavy_100k_jsonl |
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- barc0/transduction_heavy_suggestfunction_100k_jsonl |
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- barc0/transduction_rearc_dataset_400k |
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- barc0/transduction_angmented_100k-gpt4-description-gpt4omini-code_generated_problems |
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- barc0/transduction_angmented_100k_gpt4o-mini_generated_problems |
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model-index: |
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- name: engineer1-heavy-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3 |
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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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# engineer1-heavy-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3 |
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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 barc0/transduction_heavy_100k_jsonl, the barc0/transduction_heavy_suggestfunction_100k_jsonl, the barc0/transduction_rearc_dataset_400k, the barc0/transduction_angmented_100k-gpt4-description-gpt4omini-code_generated_problems and the barc0/transduction_angmented_100k_gpt4o-mini_generated_problems datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0219 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 128 |
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- total_eval_batch_size: 64 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 0.0378 | 1.0 | 3729 | 0.0330 | |
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| 0.0234 | 2.0 | 7458 | 0.0227 | |
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| 0.0116 | 3.0 | 11187 | 0.0219 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
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