This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.2227
Quadratic Weighted Kappa: 0.8432

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: 2e-05
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: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Quadratic Weighted Kappa
No log	1.0	21	1.4531	0.7630
No log	2.0	42	1.4259	0.7622
No log	3.0	63	1.2936	0.8170
No log	4.0	84	1.2508	0.8353
No log	5.0	105	1.2348	0.8469
No log	6.0	126	1.2241	0.8444
No log	7.0	147	1.2227	0.8432

Framework versions

Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.2
Tokenizers 0.19.1

Ostgot/my_awesome_model

my_awesome_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Ostgot/
my_awesome_model