This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the agenttuning_v4_15k_tag4 dataset. It achieves the following results on the evaluation set:

Loss: 0.3832

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: 5e-06
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 4
total_eval_batch_size: 4
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.5036	0.4237	100	0.4285
0.4649	0.8475	200	0.3868

Framework versions

Transformers 4.46.1
Pytorch 2.8.0+cu128
Datasets 3.1.0
Tokenizers 0.20.3

lemonhat/Llama-3.1-8B-agenttuning_v4_15k_tag4

agenttuning_v4_15k_tag4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lemonhat/
Llama-3.1-8B-agenttuning_v4_15k_tag4