metadata
base_model: unsloth/llama-3-8b-bnb-4bit
library_name: peft
license: llama3
tags:
- trl
- sft
- unsloth
- generated_from_trainer
model-index:
- name: judicial-summarization-llama-3-finetuned_mildsum_FL
results: []
judicial-summarization-llama-3-finetuned_mildsum_FL
This model is a fine-tuned version of unsloth/llama-3-8b-bnb-4bit on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7972
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: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3073 | 0.9991 | 273 | 1.4746 |
| 1.3533 | 1.9982 | 546 | 1.4690 |
| 1.1871 | 2.9973 | 819 | 1.5012 |
| 1.008 | 4.0 | 1093 | 1.5703 |
| 0.8119 | 4.9991 | 1366 | 1.6773 |
| 0.6565 | 5.9945 | 1638 | 1.7972 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1