llama3.1-8b-summarize-gpt4o-128k
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 4.0859
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0008 | 0.9990 | 519 | 2.1032 |
| 0.9747 | 2.0 | 1039 | 2.1444 |
| 0.9289 | 2.9990 | 1558 | 2.2517 |
| 0.8818 | 4.0 | 2078 | 2.4632 |
| 0.8109 | 4.9990 | 2597 | 2.7084 |
| 0.7513 | 6.0 | 3117 | 2.9358 |
| 0.7004 | 6.9990 | 3636 | 3.2769 |
| 0.6466 | 8.0 | 4156 | 3.6948 |
| 0.6132 | 8.9990 | 4675 | 3.9708 |
| 0.5965 | 9.9904 | 5190 | 4.0859 |
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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meta-llama/Llama-3.1-8B