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mistral-sum-r32a16

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mistral-sum-r32a16

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.6963

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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 20
training_steps: 100

Training results

Training Loss	Epoch	Step	Validation Loss
2.2129	0.0331	20	1.7936
1.6956	0.0663	40	1.7339
1.6454	0.0994	60	1.7078
1.6838	0.1326	80	1.7034
1.6367	0.1657	100	1.6963

Framework versions

PEFT 0.11.2.dev0
Transformers 4.42.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.19.1
Tokenizers 0.19.1

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Model tree for Taizer/mistral-sum-r32a16

Base model

mistralai/Mistral-7B-v0.1

Adapter

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Evaluation results

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