metadata
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- >-
barc0/transduction_100k_gpt4o-mini_generated_problems_seed100.jsonl_messages_format_0.3
- barc0/transduction_rearc
model-index:
- name: 100k_transduction-gpt4omini_lr1e-5_epoch3_engineering
results: []
100k_transduction-gpt4omini_lr1e-5_epoch3_engineering
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the barc0/transduction_100k_gpt4o-mini_generated_problems_seed100.jsonl_messages_format_0.3 and the barc0/transduction_rearc datasets. It achieves the following results on the evaluation set:
- Loss: 0.0372
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0424 | 0.9995 | 1054 | 0.0558 |
| 0.0272 | 2.0 | 2109 | 0.0390 |
| 0.0283 | 2.9986 | 3162 | 0.0372 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1