metadata
base_model: meta-llama/Meta-Llama-3.1-8B
datasets:
- scitldr
library_name: peft
license: llama3.1
tags:
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Summarization-QLoRa
results: []
Llama-3.1-8B-Summarization-QLoRa
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the scitldr dataset. It achieves the following results on the evaluation set:
- Loss: 2.3813
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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1968 | 0.2008 | 200 | 2.2962 |
| 2.2026 | 0.4016 | 400 | 2.3085 |
| 2.205 | 0.6024 | 600 | 2.3048 |
| 2.2028 | 0.8032 | 800 | 2.2968 |
| 2.2001 | 1.0040 | 1000 | 2.2911 |
| 1.7063 | 1.2048 | 1200 | 2.3696 |
| 1.6856 | 1.4056 | 1400 | 2.3756 |
| 1.6556 | 1.6064 | 1600 | 2.3823 |
| 1.6331 | 1.8072 | 1800 | 2.3813 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1