cls_headline_llama3_v1
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.2617
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.3038 | 0.2353 | 20 | 0.2961 |
0.2899 | 0.4706 | 40 | 0.2809 |
0.2707 | 0.7059 | 60 | 0.2714 |
0.2615 | 0.9412 | 80 | 0.2697 |
0.2357 | 1.1765 | 100 | 0.2707 |
0.2377 | 1.4118 | 120 | 0.2667 |
0.2346 | 1.6471 | 140 | 0.2662 |
0.2357 | 1.8824 | 160 | 0.2617 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Sorour/cls_headline_llama3_v1
Base model
meta-llama/Meta-Llama-3-8B-Instruct