svenwey/logdataset1000samples3epochs_llama3-1_8bit

logdataset1000samples3epochs_llama3-1

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the svenwey/LogDataset dataset. It achieves the following results on the evaluation set:

• Loss: 0.1188
• Sacrebleu Score: 95.0279
• Logmetric Score: 96.9791

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: 5e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Sacrebleu Score	Logmetric Score
0.1397	1.0	2035	0.1290	94.7160	96.6056
0.1153	2.0	4070	0.1219	94.9204	96.8607
0.1114	3.0	6105	0.1188	95.0279	96.9791

Framework versions

• PEFT 0.12.0
• Transformers 4.45.0.dev0
• Pytorch 2.4.1+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1