You can deploy this model and start earning money today!

Hiranmai49/
Llama-3.1-8B-Instruct-JudicialSummarization-mildSum-FirstLast-FinetuneMistral-7B

Name: Llama-3.1-8B-Instruct-JudicialSummarization-mildSum-FirstLast-FinetuneMistral-7B
Availability: InStock

peft

safetensors

generated_from_trainer

mistralai/Mistral-7B-Instruct-v0.3

adapter

apache-2.0

Views

No views yet

Llama-3.1-8B-Instruct-JudicialSummarization-mildSum-FirstLast-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: 6.4536

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
25.6841	1.8298	500	6.4495
25.2092	3.6597	1000	6.4182
24.7916	5.4895	1500	6.4285
24.544	7.3193	2000	6.4536

Framework versions

PEFT 0.13.2
Transformers 4.46.1
Pytorch 2.4.0+cu121
Datasets 3.0.1
Tokenizers 0.20.1

Hiranmai49/Llama-3.1-8B-Instruct-JudicialSummarization-mildSum-FirstLast-FinetuneMistral-7B

Llama-3.1-8B-Instruct-JudicialSummarization-mildSum-FirstLast-FinetuneMistral-7B

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Hiranmai49/
Llama-3.1-8B-Instruct-JudicialSummarization-mildSum-FirstLast-FinetuneMistral-7B