summarization-llama-2-finetuned

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the ssummarised/llama dataset. It achieves the following results on the evaluation set:

• Loss: 1.9292

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: 0.0001
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss
1.8379	1.0	1992	1.9292
1.8651	2.0	3984	1.9321
1.8298	3.0	5976	1.9534
1.3509	4.0	7968	1.9702

Framework versions

• Transformers 4.32.1
• Pytorch 2.0.1+cu117
• Datasets 2.19.0
• Tokenizers 0.13.3