This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.9194
Accuracy: 0.6675

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: 0.001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0047	1.0	14533	1.0080	0.6443
0.9258	2.0	29066	0.9194	0.6675

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1

dbrill1421/distilbert_mental_lora

distilbert_mental_lora

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

dbrill1421/
distilbert_mental_lora