Llama-3.1-8B-Instruct-JudicialSummarization-mildSum-textrank-FinetuneMistral-7B
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 6.4070
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 |
|---|---|---|---|
| 25.4707 | 1.8315 | 500 | 6.4030 |
| 25.1338 | 3.6630 | 1000 | 6.3762 |
| 24.6973 | 5.4945 | 1500 | 6.3957 |
| 24.4589 | 7.3260 | 2000 | 6.4070 |
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-mildSum-textrank-FinetuneMistral-7B
Base model
mistralai/Mistral-7B-v0.3
Finetuned
mistralai/Mistral-7B-Instruct-v0.3