llama3-8b-classification-gpt4o-100k2
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the llama-duo/synth_classification_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 1.7732
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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.3767 | 0.9978 | 225 | 1.7732 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for llama-duo/llama3-8b-classification-gpt4o-100k2
Base model
meta-llama/Meta-Llama-3-8B