Gueule-d-ange

aup-fullft-kto_w1_mmd-w1lam8.4e-4_mmdrho8.4e-4_kr0.1-seed1

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README

License: other

Model description

More information needed

Intended uses & limitations

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Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-06
train_batch_size: 8
eval_batch_size: 8
seed: 1
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 3.0

Training results

Framework versions

Transformers 4.57.1
Pytorch 2.12.1+cu130
Datasets 4.0.0
Tokenizers 0.22.2

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Model Details

Model Provider

Gueule-d-ange

Model Tree

Base

EleutherAI/pythia-1.4b

Fine-tuned

this model

Input Modalities

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Output Modalities

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Supported Functionality

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README

License: other

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: 1e-06
train_batch_size: 8
eval_batch_size: 8
seed: 1
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 3.0

Training results

Framework versions

Transformers 4.57.1
Pytorch 2.12.1+cu130
Datasets 4.0.0
Tokenizers 0.22.2