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

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

peft

safetensors

generated_from_trainer

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

adapter

apache-2.0

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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

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

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