Llama-3.1-8B-Instruct-JudicialSummarization-sci-textrank-FinetuneLlama3.18b
This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 6.2441
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: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
6.312 | 0.7179 | 500 | 6.3024 |
6.2191 | 1.4358 | 1000 | 6.2649 |
6.2087 | 2.1536 | 1500 | 6.2514 |
6.2002 | 2.8715 | 2000 | 6.2441 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for Hiranmai49/Llama-3.1-8B-Instruct-JudicialSummarization-sci-textrank-FinetuneLlama3.18b
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct